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volume 7, Article number: 325 (2026) Cite this article
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Photovoltaic energy is expected to lead renewable energy growth, but rising solar energy penetration increases vulnerability to climate-driven intermittency. Here, we examine how the El Niño-Southern Oscillation, the dominant source of seasonal-to-interannual climate variability, affects photovoltaic power output. Using four decades of reanalysis data, we show that El Niño events reduce surface solar irradiance, causing sustained solar energy deficits in regions with growing solar energy penetration, including California, the southern Atacama Desert, the Chaco Basin, the Middle East, and East China. These impacts are especially pronounced during rare Super El Niño events, of which only three have occurred since the early 1980s. Our analysis indicates that future Super El Niño events could significantly lower photovoltaic generation, increase reliance on fossil fuel backup, and temporarily raise carbon dioxide emissions by tens of millions of tons.
Photovoltaic (PV) power remains the primary driver of the renewable energy transition, accounting for over 75% of new renewable capacity installed in 2023 and nearly 60% of the electricity generated from newly added renewables worldwide¹. Global cumulative PV capacity rose from 1.1 TW in 2022 to approximately 1.5 TW in 2023². Rapid PV expansion in key regions (Fig. 1a, b) has pushed PV penetration to around 10% in China and the European Union (EU)¹. While PV meets over 8% of global electricity demand, solar power has supplied 100% of electricity for several hours in parts of Australia and Chile¹. PV is expected to remain the primary driver of renewable energy growth. Under a low-emission scenario, global PV generation could increase 60-fold by mid-century³.
a Cumulative installed photovoltaic (PV) capacity (upper panel) and the cumulative number of PV power plants with a capacity >100 MW (lower panel) in China, the EU, and the USA. China’s PV installations surged in 2023, reaching a record annual growth of ~215 GW—over 60% of new global capacity built that year—and bringing China’s cumulative PV capacity to more than 600 GW. The European Union (EU) also installed a robust ~50 GW in 2023, and the USA installed >30 GW that year. Collectively, these regions (China, the EU, and the USA) accounted for two-thirds of global PV generation in 2023 and are expected to drive PV expansion in the coming decades. b Total utility-scale photovoltaic (PV) power plants existing in 2024. Each dot represents a power plant with a capacity >20 MW. China, the EU, the USA, Japan, and India exhibit the largest density of utility-scale PV power plants. The key Niño 3.4 region (5°N–5°S, 170°W–120°W) is also highlighted in the plot. c Annual mean of the photovoltaic potential (PV_POT) computed over the period 1982–2024. Data on PV capacity in plot (a) (upper panel) are sourced from the International Renewable Energy Agency (IRENA) renewable capacity statistics², available at https://www.irena.org/Publications/2024/Mar/Renewable-capacity-statistics-2024. Data on PV power plants in plots (a) (lower panel) and b are sourced from the Global Energy Monitor⁷⁵, available at https://globalenergymonitor.org/projects/global-solar-power-tracker/. PV_POT data in plot c were calculated using the ERA5 reanalysis dataset⁷⁷, available at https://www.ecmwf.int/en/forecasts/datasets/reanalysis-datasets/era5. Plots were generated using Python’s Matplotlib library, version 3.4.3, available at https://matplotlib.org/3.4.3/contents.html.
As PV systems reach higher penetration levels in more countries, managing PV intermittency becomes increasingly challenging. These fluctuations in PV power output complicate grid balancing by causing mismatches between resource availability and electricity demand, thereby impacting system reliability^4,5. While diurnal and seasonal cycles drive intermittency on timescales from hours to months^5,6, weather and climate variability influence PV power outputs on timescales from seconds to years⁷. By altering surface shortwave (SW) irradiance, both weather and climate variability play a crucial role in PV intermittency^8,9,10.
Climate change is expected to exacerbate PV intermittency in some regions through extreme weather and enhanced climate variability^11,12. Climate-induced deficits in PV power output, often called energy droughts, can last from days to months^{12,13,14,15,16,17} and may trigger forced oscillations, thermal runaway, frequency and voltage disturbances, and heightened grid instability risks⁷. While recent research has focused on short-term (hour-to-day) solar resource variability^18,19, less attention has been given to the broader impacts of seasonal-to-interannual variability driven by large-scale climate modes.
Enhanced climate variability is not always man-made. Natural climate modes, such as the El Niño–Southern Oscillation (ENSO), can also amplify PV intermittency by modulating regional climate patterns worldwide²⁰. ENSO is a fluctuation in sea surface temperature (SST) and atmospheric pressure across the equatorial Pacific²¹. During El Niño, weakened trade winds cause warm water to accumulate in the tropical Pacific. In contrast, La Niña strengthens trade winds, increasing upwelling and bringing cold, nutrient-rich water to the surface²¹. Through atmospheric teleconnections, ENSO phases influence seasonal-to-interannual solar resource variability in South America^22,23, Australia²⁴, Africa²⁵, Texas²⁶, California^15,27, and even Europe, where ENSO has been linked to fluctuations in the EU renewable energy stock market²⁸. While low PV penetration has so far limited ENSO-driven disruptions to the energy grid, this situation is poised to change rapidly.
As PV systems reach higher penetration levels, electricity grids are becoming more vulnerable to disruptions from El Niño and La Niña events, especially during rare Super El Niño occurrences, only three of which have been recorded since the early 1980s²⁹. Super El Niño events are typically defined by SST anomalies of at least 2 °C in the Niño 3.4 Region (5°N–5°S, 170°–120°W, Fig. 1b)^30,31, as identified by the National Oceanic and Atmospheric Administration (NOAA)³². While Super El Niño events are well known for their severe socioeconomic consequences^33,34,35,36, their impact on increasingly PV-dependent energy grids remains largely unexamined. During the last Super El Niño in 2015–2016, global installed PV capacity was nearly ten times lower than today.
Here, we used reanalysis datasets from 1982 to 2024 to reconstruct the PV power response to El Niño and La Niña events (i.e., positive and negative SST anomalies in the equatorial Pacific, respectively). As a proxy for PV power output, we used the PV potential (PV_POT), defined as the ratio of a PV module’s power output under standard test conditions to its actual output in the field^{12,37,38,39,40,41}. PV_POT primarily depends on surface SW irradiance, which is influenced by aerosols^42,43,44 and cloud cover^45,46. PV_POT is also affected by air temperature (cooler conditions generally improve PV cell performance⁴⁷) and surface wind speed (stronger airflow enhances module cooling⁴⁸). In spite of these other factors, SW irradiance remains the dominant factor, and that explains why annual mean PV_POT (Fig. 1c) closely mirrors annual mean surface SW irradiance (Fig. S1). Our findings show that El Niño (La Niña) negatively (positively) affects surface solar irradiance, leading to persistent PV energy deficits (surpluses) in regions with increasing PV penetration, including parts of China, the USA, and South America. These results underscore the importance of accounting for ENSO-driven variability when developing climate-resilient PV-based grids.
El Niño and La Niña events significantly affect factors that influence PV cell performance, including solar irradiance, air temperature, and surface wind speed. While NOAA’s Climate Prediction Center (CPC) monitors several equatorial Pacific regions, including Niño 3 (eastern Pacific), Niño 4 (central Pacific), and Niño 1 + 2 (off the Peruvian coast), El Niño and La Niña events are defined based on SST anomalies in the Niño 3.4 region³². During El Niño events, SST in the tropical central Pacific (specifically, the Niño 3.4 region) can rise by several degrees Celsius, even exceeding 2 °C during Super El Niño events (Fig. S2). This warming is accompanied by an annual average temperature increase of up to 1 °C over the basin’s warmest waters (Fig. 2a, upper panel) and increased cloud cover. During Super El Niño events, annual average surface SW irradiance over the Niño 3.4 region can decrease by more than 15 W m⁻² (Fig. 2a, lower panel). During La Niña, the Niño 3.4 region cools, and the basin’s warmest waters shift closer to Indonesia and the western Pacific. This redistribution disrupts atmospheric circulation²¹, altering climate patterns, including air temperature (Fig. 2b), surface wind speed (Fig. S3), and solar irradiance (Fig. 2c) across many regions.
a Surface air temperature (upper panel) and surface shortwave (SW) irradiance (lower panel) in the Niño 3.4 Region relative to the 1982–2024 mean. The red-shaded columns highlight the Super El Niño events of 1982–1983, 1997–1998, and 2015–2016. Pearson correlation between the 12-month average sea surface temperature (SST) anomalies in the Niño 3.4 region and the corresponding 12-month average of the: b surface air temperature, and c surface irradiance. Data for the period 1982–2024 were analyzed. Stippling in b and c indicates statistical significance. The 12-month averages of surface air temperature, surface irradiance, and SST in plots b and c are calculated from September to August of the following year. Surface irradiance and surface temperature data come from the ERA5 reanalysis⁷⁷ available at https://www.ecmwf.int/en/forecasts/datasets/reanalysis-datasets/era5. SST anomalies in the Niño Regions come from the https://www.cpc.ncep.noaa.gov/data/indices/wksst9120.for⁷⁴. Plots were generated using Python’s Matplotlib library (version 3.4.3), available at https://matplotlib.org/3.4.3/contents.html.
The interannual variability of air temperature, surface SW irradiance, and surface wind speed around the world is influenced by year-to-year changes in SST in the tropical central Pacific. We found a strong correlation between SST anomalies in the Niño 3.4 Region and the air temperature across large areas, including tropical South America (particularly across the Amazon Basin), southern Africa, Australia, and Southeast Asia (Fig. 2b). This correlation indicates that El Niño events are associated with spikes in air temperature in these regions, while La Niña events generally bring cooler conditions. We also found a significant anticorrelation between SST anomalies in the Niño 3.4 Region and the surface SW irradiance across large parts of southern South America (including the southern Atacama Desert and the Chaco Basin), North America, the Middle East, and the Sahara (Fig. 2c). This suggests that La Niña events typically result in sunnier conditions, whereas El Niño events are linked to substantial decreases in surface SW irradiance in these regions. As shown in Fig. S3, anomalies in SST in the Niño 3.4 Region also significantly affect surface wind speed over vast areas of the planet.
The impacts of El Niño and La Niña events are typically strongest during December–January–February (DJF). El Niño usually peaks in December, explaining the strong correlation between DJF SST anomalies in the Niño 3.4 Region and DJF air temperatures across much of the globe in both hemispheres. While the effects are particularly pronounced in tropical South America, most regions also experience warmer conditions during the austral summer (DJF) under El Niño events (Fig. S4). In tropical South America, the correlation between SST anomalies and air temperatures remains strong during March–April–May (MAM) but weakens in other seasons (Fig. S4). Similarly, correlations between DJF SST anomalies in the Niño 3.4 Region and DJF SW irradiance are significant in most of the Amazon Basin, southern Africa, western Australia, and Southeast Asia (Fig. S5). However, El Niño’s effects on SW irradiance show more regional variation than its effects on air temperature. For instance, during DJF, some areas (e.g., the Amazon Basin) experience sunnier conditions, while others (e.g., the Horn of Africa) become cloudier (Fig. S5d). The complexity of the climate system is further underlined by the fact that correlations can weaken or even reverse during different seasons. For example, in the Horn of Africa, El Niño events can lead to cloudier conditions during DJF (Fig. S5d) and sunnier conditions during boreal summer (June–July–August, JJA) (Fig. S5b).
The atmospheric response to ENSO events is driven by circulation anomalies that ultimately modulate temperature (Fig. 2b), cloudiness and surface solar radiation (Fig. 2c). During El Niño, the Walker circulation weakens, generating an anomalous anticyclone over the western North Pacific that enhances southerly moisture transport into East China and strengthens subsidence-induced cloud formation along its western flank⁴⁹. The combined effect is a marked increase in low-level cloudiness and a corresponding reduction in surface solar irradiance over East China. El Niño conditions also shift the Pacific jet stream southward and intensify subtropical westerlies, steering more frequent extratropical cyclones toward California²¹. This increases both deep and low-level cloud cover, especially in boreal winter, reducing the occurrence of clear-sky conditions. A similar mechanism operates along the southeast Pacific margin: weakening of the South Pacific subtropical anticyclone, combined with enhanced zonal flow, leads to increased storm-track activity over southern South America³³. These changes produce cloudier and wetter conditions during winter and spring, directly suppressing surface solar radiation. While El Niño also enhances cloudiness and storm activity over the Levant and the Middle East⁵⁰, convection over the western Pacific weakens substantially, producing anomalous subsidence over eastern Australia⁵¹. This downward motion suppresses cloud formation, particularly reducing deep convective clouds associated with the Australian monsoon and subtropical rainfall systems.
The interannual variability of PV potential exhibits the signature of El Niño and La Niña events. In regions that include northern California and southern Brazil, PV_POT values have dropped substantially during El Niño events, particularly during the Super El Niño events of 1982–1983, 1997–1998, and 2015–2016. These drops are most noticeable during the austral summer (DJF), as the largest anomalies associated with El Niño events occur around the end of the year and the beginning of the following year (Fig. 3a). In northern California, DJF PV_POT values dropped by more than 10% during Super El Niño events (Fig. 3a, upper panel). In contrast, northern California experienced sharp increases in PV_POT during strong La Niña events such as those in 1984–1985, 1988–1989, 2011–2012, and 2021–2022 (Fig. 3a, upper panel). Similar, but less pronounced, drops and spikes in DJF PV_POT values occurred in southern Brazil (Fig. 3a, lower panel). The impacts of El Niño and La Niña events on PV_POT are also relevant in many other regions.
a DJF PV potential (PV_POT) relative to the 1982–2024 mean in northern California (upper panel) and southern Brazil (lower panel). The red-shaded columns highlight the Super El Niño events of 1982–1983, 1997–1998, and 2015–2016. Southern Brazil includes the states of Rio Grande do Sul, Santa Catarina, Paraná, São Paulo, and Rio de Janeiro. Northern California includes the counties of Del Norte, Humboldt, Siskiyou, Modoc, Trinity, Shasta, Lassen, Mendocino, Tehama, Plumas, Lake, and Sierra. Pearson correlation between the 12-month average PV potential (PV_POT) and the corresponding 12-month average sea surface temperature (SST) anomalies in: b the Niño 3.4 region (5°N–5°S, 170°W–120°W), and c the Niño 1 + 2 region (0–10°S, 90°W–80°W). Data for the period 1982–2024 were analyzed. Stippling in plots b and c indicates statistical significance. The 12-month averages of PV_POT and SST in plots b and c are calculated from September to August of the following year. The PV potential (PV_POT) was calculated using data from the ERA5 reanalysis⁷⁷ available at https://www.ecmwf.int/en/forecasts/datasets/reanalysis-datasets/era5. SST anomalies in the Niño Regions come from the Climate Prediction Center (CPC), part of the National Oceanic and Atmospheric Administration (NOAA), available at https://www.cpc.ncep.noaa.gov/data/indices/wksst9120.for⁷⁴. Plots were generated using Python’s Matplotlib library (version 3.4.3), available at https://matplotlib.org/3.4.3/contents.html.
Year-to-year changes in PV potential are influenced by the interannual variability of tropical Pacific SST. Across areas with high solar potential, there are significant correlations (either positive or negative) between SST anomalies in the Niño 3.4 region and PV_POT values (Fig. 3b). Regions with positive correlations are expected to see increases in PV_POT during El Niño events, likely due to sunnier conditions resulting from significant reductions in cloud cover. This is the case of southern Africa, eastern Australia, Southeast Asia, and the Amazon Basin (Fig. 3b). These increases are expected despite the fact that these regions will also experience significant spikes in air temperature during El Niño events that negatively affect PV cell performance (Fig. 2b). The strong positive correlations in the case of southern Africa, eastern Australia, Southeast Asia, and the Amazon Basin (Fig. 3b) highlight that the reduction in cloudiness and the resulting increase in solar irradiance during El Niño events have a much stronger influence on PV_POT than the temperature rise. Regions with negative correlations are expected to see increases in PV_POT during La Niña events. This is the case of southern Brazil, the Middle East, and southern and western USA (Fig. 3b). Conversely, these same regions are likely to experience decreases in PV_POT during El Niño events.
The PV potential is influenced by changes in SST in various Niño regions, including the Niño 1 + 2 region (off the western coast of Peru), the Niño 3 region (eastern Pacific), and the Niño 4 region (central Pacific). In most countries, correlations between SST anomalies in these regions and PV_POT values (Fig. 3c and S6a, b) are slightly weaker compared to the Niño 3.4 region (Fig. 3b). A notable exception is East China, where the correlation between SST anomalies in the Niño 1 + 2 region PV_POT values (Fig. 3c) becomes slightly stronger compared to the Niño 3.4 region (Fig. 3b). Nevertheless, regardless of which Niño region is used in the comparison, the areas showing the strongest correlations (whether positive or negative) are located in North and South America, particularly California, the southern Atacama Desert, central Chile, the Amazon Basin, and the Chaco region. As shown in Fig. 3c, the Amazon Basin is expected to see increases in PV_POT during warming events in the Niño 1 + 2 region, typically associated with eastern Pacific (EP) El Niño events³³. Conversely, California, the southern Atacama Desert, Central Chile, and the Chaco Basin (including southern Brazil and northern Argentina) are expected to experience declines in PV_POT during EP El Niño events. While SST anomalies in the Niño regions are often coupled (Fig. S2), fluctuations in the Niño 1 + 2 region tend to be stronger and more frequent than those in the other Niño regions⁵². For instance, the 2023–2024 El Niño was a strong event, particularly in the Niño 1 + 2 region⁵³ (Fig. S2). However, the associated atmospheric response (specifically, changes in atmospheric pressure) was substantially weaker than those observed during the canonical Super El Niño events of 1982–1983, 1997–1998, and 2015–2016. The concurrent strong warming in the Atlantic and Indian Oceans was crucial in dampening the atmospheric response during the 2023 El Niño⁵⁴, clearly distinguishing its impacts from those of the other three strong El Niño events. Nevertheless, the strong correlations in (Fig. 3c and S6a, b) underscore the influence of ENSO-driven fluctuations in tropical Pacific SSTs on the PV intermittency across large portions of the globe.
In vast regions of the planet, the effects of El Niño and La Niña events on PV potential are significant regardless of the season. For the austral spring (SON) and summer (DJF), we found relatively strong correlations (either negative or positive) between PV_POT and SST anomalies in the Niño 3.4 Region across parts of South America (in particular across the Amazon Basin and the Chaco Basin), the Horn of Africa, Australia, Southeast China, and mainland Southeast Asia (Fig. S7). The correlations weaken across the Chaco Basin, Horn of Africa, Australia, Southeast China, but strengthen in mainland Southeast Asia during the austral fall (MAM) (Fig. S7a). The complexity of the climate system is further highlighted by shifts in correlations across regions and changes in sign during different seasons. For instance, the effects of SST fluctuations in the Niño 3.4 Region shift from eastern Australia in the austral spring (Fig. S7c) to western Australia in the austral summer (Fig. S7d). In the Horn of Africa, El Niño events can reduce PV_POT during the austral summer (DJF) (Fig. S7d) and increase it during the boreal summer (JJA) (Fig. S7b). Regional patterns remain similar in the case of correlations between PV_POT and SST anomalies in the Niño 1 + 2 Region (Fig. S8).
Our assessment of the impacts of the next Super El Niño event is based on the effects observed during past canonical Super El Niño episodes, under the assumption that the next event will likely exhibit similar large-scale characteristics. Relative to the 1982–2024 period, 12-month PV_POT anomalies during the three most recent Super El Niño events (1982–1983, 1997–1998, and 2015–2016) averaged over +5% in parts of the Amazon Basin and approached −10% in parts of East China and the Chaco Basin (including southern Brazil and northern Argentina) (Fig. 4a). Positive anomalies indicate PV power surpluses (i.e., energy oversupply), while negative anomalies signal PV deficits (i.e., energy undersupply). Both can amplify intermittency, leading to grid congestion in the case of oversupply or increasing the need for backup and stabilization services during undersupply. In East China, negative anomalies were particularly intense in the provinces of Hunan, Guangdong, and Fujian, as well as in the Guangxi Zhuang Autonomous Region. Although less severe than in East China, negative anomalies also dominate in California, the southern Atacama Desert, and Central Chile (Fig. 4a). In parts of California and Central Chile, regions with high PV penetration and where the influence of El Nino is well established, 12-month PV_POT anomalies during the three most recent Super El Niño events approached −5% (Fig. 4a).
a A 12-month PV Potential (PV_POT) anomalies averaged during the Super El Niño events (1982–1983, 1997–1998, and 2015–2016), relative to the 1982–2024 period. A 12-month positive anomalies suggest an increase in PV power output (i.e., energy over-production), while a 12-month negative anomalies indicate a decrease in PV power output (i.e., energy under-production). b 12-month PV_POT droughts derived from the 12-month PV_POT anomalies in (a). A mild, moderate, or severe drought is defined as a 12-month period in which PV potential (PVPOT) falls below the 30th, 20th, or 10th percentile, respectively, of the historical distribution for the same calendar period. We used data from 1982 to 2024 to compute these percentile thresholds. Stippling in plot a indicates statistical significance according to the two-sided Welch’s t-test. The 12-month PV_POT anomalies in plot (a) and the 12-month PV_POT droughts in plot (b) are calculated from August to July of the following year. Accordingly, we used the Super El Niño years 1982, 1997, and 2015 for the ASOND months and the Super El Niño years 1983, 1998, and 2016 for the JFMAMJJ months. PV_POT values were calculated using data from the ERA5 reanalysis⁷⁷ available at https://www.ecmwf.int/en/forecasts/datasets/reanalysis-datasets/era5.
Expected Super El Niño–induced PV_POT anomalies are substantial enough to trigger multi-month solar energy droughts in vast regions. Seasonal and multi-month droughts in solar energy remain an emerging concept, with definitions varying widely across studies^55,56,57. Traditional production-based metrics¹⁶ define energy droughts as uninterrupted sequences of days with anomalously low power production; however, these definitions were originally developed to characterize short-term (hour-to-day) fluctuations in solar resource availability. Here, we adopt the multi-month energy-drought thresholds proposed by Allen & Otero⁵⁵, which classify moderate (severe) droughts as periods when energy potential falls below roughly the 20th (10th) percentile of the historical distribution for that same period. Using these thresholds and relative to the 1982–2024 climatology, our results indicate that the next Super El Niño event could produce 12-month PV droughts ranging from moderate to severe across large regions of East China, the Chaco Basin (including southern Brazil and northern Argentina), California, the southern Atacama Desert and Central Chile, as well as in the southern Arabian Peninsula (Fig. 4b).
The impact of Super El Niño events on PV power output varies by season. During the three most recent Super El Niño events (1982–1983, 1997–1998, and 2015–2016), PV_POT in some provinces of East China dropped by up to −15% during boreal fall (SON) (Fig. S9). During the boreal summer (JJA), when solar yield typically peaks in the Northern Hemisphere, the declines in PV_POT in East China were less pronounced, yet still significant (~−5%) in the southeastern provinces (Fig. S9b). In California, PV_POT anomalies remain negative year-round during Super El Niño events, with declines ranging from around −3% during the boreal summer (Fig. S9b) to about −10% during the boreal winter (Fig. S9d). In the southern Atacama Desert, Central Chile, and the Chaco Basin (including southern Brazil and northern Argentina), PV_POT anomalies approached −10% during the austral fall (MAM) (Fig. S9a) and the austral winter (JJA) (Fig. S9b) but considerably weakened during the austral summer (DJF) (Fig. S9d).
The intensity of a Super Niño’s effects is not always the same. In some provinces of East China, 12-month PV_POT anomalies during the 1997–1998 Super El Niño approached −15% (Fig. S10), whereas they were much weaker (around −5%) during the most recent Super El Niño event. In California and the Chaco Basin, the decline in the 12-month PV_POT was markedly deeper during the 1982–1983 and 1997–1998 events than during the 2015–2016 event (Fig. S10). Regarding positive anomalies, Super El Niño events consistently led to the largest spikes in 12-month PV_POT values (up to +10%) in the Amazon Basin (Fig. S10). While significant in many regions, the anomalies from the three most recent Super El Niño events (1982–1983, 1997–1998, and 2015–2016) had minimal impact on the electrical grid due to low PV penetration at the time. When the 2015–2016 event occurred, global installed PV capacity was nearly ten times lower than today. As PV systems continue to expand, the energy grid is becoming increasingly susceptible to disruptions associated with Super El Niño events.
The expected rise in PV penetration will increase the grid’s vulnerability to Super El Niño events. Under a low-emission scenario, global PV generation is projected to grow 60-fold by mid-century compared to current levels³. By 2035, PV generation in East China, California, Argentina, and Chile is expected to increase by at least tenfold compared to 2023 levels (Fig. 5a, upper panel). At the same time, rising PV penetration will reduce carbon intensity, the amount of CO₂ emitted per unit of electricity generated. The International Energy Agency (IEA) projects significant reductions in carbon intensity worldwide in the coming years⁵⁸. Based on announced pledges and net-zero scenarios, East China’s electricity carbon intensity is expected to fall by half, while in California, Argentina, and Chile, it is projected to approach zero within the next decade (Fig. 5a, lower panel). Among major PV-producing regions (China, the EU, the USA, India, South Korea, Australia, Brazil, Chile, and Japan) only China and India have not committed to carbon neutrality by 2050 or earlier⁵⁸. Tables S1 and S2 provide data on 2023 levels and future projections for PV generation and carbon intensity in key regions and countries.
a PV generation (upper panel) and carbon intensity (lower panel) in East China, California, Chile, and Argentina. In these regions with high PV penetration, the influence of El Niño is well established. In this study, East China includes the provinces of Anhui, Fujian, Guangdong, Guizhou, Hainan, Hebei, Heilongjiang, Henan, Hubei, Hunan, Jiangsu, Jiangxi, Jilin, Liaoning, Shandong, Shanxi, Yunnan, and Zhejiang; the autonomous region of Guangxi Zhuang; the direct-controlled municipalities of Beijing, Chongqing, Shanghai, and Tianjin; as well as the special administrative region of Hong Kong. Data for other regions and countries of interest are shown in Tables S1 and S2. b Expected impacts of next Super El Niño event on PV Potential (upper panel) and on CO₂ Emissions (lower panel) in East China, California, Chile, and Argentina. The range of values in the upper panel is defined by the maximum and minimum anomalies observed in these countries and regions during the Super El Niño events of 1982–1983, 1997–1998, and 2015–2016 (Fig. S10). For Chile, the expected impacts were averaged over the area between 23°S and 37°S, which includes the southern Atacama Desert and Central Chile and where the country’s PV capacity is located. For Argentina, the estimates are averaged over the region north of 35°S, which contains the vast majority of its PV capacity. Data for other regions and countries of interest are shown in Tables S3 and S4. Boxplots in the lower panel are based on the simulations shown in Fig. S11. In each box, the central mark (white stripe) indicates the median, and the edges indicate the 25th and 75th percentiles. The whiskers extend to the maximum and minimum data, excluding outliers. Results for other regions and countries of interest are shown in Table S5. Carbon intensity and PV generation data for 2023 come from Ember´s Yearly Electricity Data (https://ember-energy.org/data/yearly-electricity-data/). In the case of East China, PV generation was derived from provincial-scale PV generation, sourced from the Chinese National Energy Administration (https://www.nea.gov.cn/2024-02/28/c_1310765696.htm). Projections of the carbon intensity are based on announced pledges and net-zero scenarios⁵⁸. Projections of the PV generation are derived from the REMIND_EU 2.0 model, assuming the optimistic NewPl_1.5scenario³. Plots were generated using Python’s Matplotlib library (version 3.4.3), available at https://matplotlib.org/3.4.3/contents.html.
The next Super El Niño event will likely reduce PV generation in key regions. While such events can lead to increases in PV output (i.e., energy oversupply) in some areas, they also lead to significant decrease (i.e., energy undersupply) in others, such as East China, California, the southern Atacama Desert, Central Chile, and the Chaco Basin (including southern Brazil and northern Argentina) (Fig. 4a). Although the frequency of Super El Niño events is expected to increase in the 21 st century⁵⁹, they have historically occurred approximately every 15–20 years, suggesting that the next event could occur before 2035. While the impacts of the next Super El Niño on PV generation remain uncertain, insights can be drawn from the three most recent events (1982–1983, 1997–1998, and 2015–2016). For instance, the maximum and minimum PV_POT anomalies observed during these events (Tables S3 and S4) can be used to estimate the likely range of PV_POT reductions for the next Super El Niño. While the expected 12-month PV generation reductions can reach up to approximately 5% in California (Table S3), the 12-month PV_POT can decline by nearly 10% in some southeastern Chinese provinces, such as Guangdong, Jiangxi, and Fujian (Table S4). Figure 4c (upper panel) shows the expected range of 12-month PV generation declines during the next Super El Niño for East China, California, Argentina (averaged for the region north of 35°S), and Chile (averaged over the area between 23°S and 37°S, which includes the southern Atacama Desert and Central Chile). While the next Super El Niño could reduce the 12-month PV_POT by more than 8% in northern Argentina (Fig. 5b, upper panel), the effects may be particularly consequential in China. In the provinces of East China—home to nearly 90% of the country’s population—a Super El Niño could collectively reduce the 12-month PV_POT by more than 4% (Fig. 5b, upper panel), potentially leading to temporary energy deficits and increased emissions from backup energy sources.
Super El Niño events can temporarily increase carbon emissions by reducing PV generation in key regions. The impact on CO₂ emissions can be estimated by multiplying the expected decreases in PV generation by the carbon intensity of the affected country or region. This estimate assumes that ENSO-driven PV undersupply will be compensated by a mix of available backup sources rather than exclusively by carbon-intensive power plants (e.g., coal-fired plants). However, this assessment involves significant uncertainties. The exact timing of the next Super El Niño is unknown, as are the actual PV generation and carbon intensity levels at the time of the event. To account for these uncertainties, here we conducted Monte Carlo simulations to estimate the potential CO₂ emissions impact (Fig. S11). These simulations involved recursively computing the expected additional CO₂ emissions using large sets of previously generated values for carbon intensity and ENSO-driven PV undersupply (Fig. S11). Our simulations suggest that the next Super El Niño could temporarily increase CO₂ emissions by tens of millions of tons in regions with growing PV penetration, such as East China, California, Argentina, and Chile (Fig. 5b, lower panel). Most of these additional emissions are expected in East China, not only because it is one of the world’s most ENSO-sensitive regions but also because its carbon intensity is projected to decline more slowly than in California, Argentina, and Chile (Fig. 5a, lower panel). To compensate for the energy gap left by the next Super El Niño, China will likely still need to rely on carbon-intensive power plants as part of its backup energy mix.
El Niño and La Niña significantly amplify PV intermittency across vast regions of the planet. Our findings illuminate the impact of ENSO phases (i.e., El Niño and La Niña) on the seasonal-to-interannual variability of solar resources and PV power output. Using reanalysis datasets spanning four decades, we found that El Niño (La Niña) negatively (positively) affects surface solar irradiance, leading to season-spanning PV energy deficits (surpluses) in regions with increasing PV penetration, such as California, the southern Atacama Desert, the Chaco Basin, the Middle East, and East China. From both a reliability and financial perspective, persistent energy deficits (surpluses) are critical, as they can drive spot market prices up (down)²⁶.
Super El Niño events can cause prolonged and severe PV deficits in key regions. As PV penetration rates rise, energy grids are becoming more vulnerable to ENSO-induced disruptions, particularly during Super El Niño events. Our analyses indicate that Super El Niño events can lead to season-spanning PV energy deficits of up to 10% across parts of East China, one of the world’s most populated and PV-intensive regions. While low PV penetration previously shielded the grid from ENSO-induced disruptions, the situation is rapidly changing. Since the most recent Super El Niño event in 2015–2016, China’s installed PV capacity has grown nearly fifteenfold. As PV penetration continues to increase, ENSO-driven PV intermittency will have greater implications for energy security, grid stability, and carbon emissions.
Super El Niño events can temporarily increase carbon emissions. By reducing PV generation in key regions, ENSO events can increase dependence on backup power, often from fossil fuels. We found that the next Super El Niño event could temporarily boost CO₂ emissions by dozens of millions of tons. Most of these additional emissions will likely occur in East China, where PV penetration is growing rapidly, but coal is expected to remain a major part of the energy mix for at least the next two decades⁵⁸. While Super El Niño events may also reduce PV generation in regions of Europe and the U.S., the impact on emissions is expected to rapidly diminish as these regions transition to lower-carbon backup solutions. In affected regions, mitigating emissions from ENSO-driven PV intermittency will require enhanced energy storage and greater capacity redundancy.
The effect of eventual feedback loops between climate change and ENSO on solar resources remains uncertain. While climate change is expected to increase PV intermittency in some regions due to enhanced climate variability and extreme weather^11,12, how ENSO itself may change under future greenhouse warming is still unclear⁶⁰. Climate models suggest that under a likely emissions scenario, extreme El Niño frequency increases linearly with global mean temperature, doubling at 1.5 °C warming⁶¹. The frequency of Super El Niño events is projected to double in the 21st century, potentially occurring once every 10 years instead of every twenty⁵⁹. Beyond the 21st century, however, climate-driven ENSO amplification may weaken or even reverse due to a collapse in equatorial Pacific upwelling⁶². Under high-emission scenarios, ENSO variability after 2100 may decrease from its earlier enhanced state to amplitudes smaller than those of the 20th century⁶³. These projected climate-driven changes in ENSO highlight the importance of explicitly incorporating ENSO-related seasonal-to-interannual variability into the planning and design of climate-resilient PV-dominated electricity systems.
Overcoming ENSO-driven disruptions will require policies and investment. Recognizing the need to integrate climate extremes and extreme weather into energy planning and management is becoming increasingly widespread⁶⁴. Our findings emphasize that managing ENSO-driven PV intermittency in high-penetration regions will likely require proactive curtailment⁶⁵, demand response⁶⁶, and policies promoting energy storage⁶⁷; China’s mandatory coupling of storage with solar has already led to record deployment volumes¹. While technological advances can help mitigate ENSO-driven PV intermittency, wide geographical distribution remains the simplest way to counteract the effects of enhanced climate variability.
Distributed generation and geographical diversity offer a feasible approach to accommodating high PV penetration and enhanced intermittency. As the energy system transitions toward greater reliance on PV, ensuring energy security requires overcoming local variability. When solar power is deployed over a large geographical area with significant time zone differences, intermittency is significantly reduced⁶⁸, along with electricity market balancing costs⁶⁹. By mapping the spatial footprint of ENSO-driven disruptions, we provide essential insights for energy planners to develop climate-resilient PV deployment strategies.
The strong regional dependence of ENSO-induced variability highlights the need for location-specific climate risk assessments in energy planning and the entwinement of energy systems with knowledge infrastructures. Future research should focus on improving seasonal and interannual climate forecasting to anticipate ENSO-driven PV disruptions and understanding how ENSO interacts with other climate modes, such as regional monsoons and large-scale circulation patterns. Additionally, strengthening the role of low-carbon dispatchable energy sources to mitigate PV undersupply will be crucial for minimizing excess emissions in regions negatively affected by ENSO events. A deeper integration of climate science into energy planning is essential for ensuring the long-term stability and sustainability of solar-powered energy systems.
The PV potential (PV_POT) is defined as the ratio of the power output under standard test conditions to the power output a PV module can achieve in the field^{12,37,38,39,40,41}:
where I_STC represents the shortwave (SW) irradiance under standard test conditions (1000 W m⁻²), I is the SW irradiance reaching the PV module in the field, and P_R is the performance ratio, which accounts for the impact of the cell temperature (T_cell) on the module’s efficiency. According to earlier studies¹², P_R can be calculated as follows:
where T_STC is typically 25 °C, and γ is 0.005 °C⁻¹ for monocrystalline silicon cells^70,71. According to Eq. (2), higher cell temperatures reduce the performance ratio. The cell temperature, T_cell, depends on air temperature (T) and surface wind speed (v). Following prior efforts^41,48, T_cell can be estimated as:
where c₁ = 4.3 °C, c₂ = 0.943, c₃ = 0.028 °C W⁻¹ m² and c₄ = 1.528 °C m⁻¹s. Equation (3) shows that increased wind speed enhances PV module cooling, leading to a lower cell temperature and, consequently, a higher performance ratio.
Although I, v and T change during the day, here we used monthly averages from the ERA5 reanalysis dataset (available at https://www.ecmwf.int/en/forecasts/datasets/reanalysis-datasets/era5) to compute monthly PV_POT values. Specifically, in Eq. (3), I corresponds to the monthly average of downwelling SW irradiance, v to the monthly average of surface wind speed, and T to the monthly average of surface air temperature. Our results are constrained by the spatial resolution of the ERA5 reanalysis data. Regional estimates (e.g., Northern California and East China) are based on spatial averages within those regions.
Despite its limitations, PV_POT is a widely used and well-established proxy for PV power output^{12,37,38,39,40,41}. The absolute magnitude of PV_POT depends on the accuracy of the inputs in Eq. (1) and on the empirical coefficients in Eqs. (2) and (3), which may differ slightly from those used in PV modules deployed in various regions. These differences can introduce small biases in absolute values. However, they affect all calculations in a systematic manner and therefore have only a minor influence on anomalies or relative deviations computed with respect to a reference period. Because the ENSO-induced PV response arises from changes in irradiance and temperature rather than from module-specific characteristics, PV_POT is well-suited to assess the relative PV potential changes that are the focus of this study. This is consistent with previous research where PV_POT has been shown to reliably capture the climate-driven variability in PV output^{12,37,38,39,40,41}.
Monitoring of ENSO conditions by NOAA’s Climate Prediction Center (CPC) primarily focuses on sea surface temperature (SST) in several geographic regions of the equatorial Pacific including the Niño 1  +  2 Region (right in front of the western coast of Peru), the Niño 3 Region (eastern Pacific), the Niño 4 Region (central Pacific), and the Niño 3.4 Region. In this study, we analyzed SST anomalies in El Niño regions produced by NOAA’s CPC, available at https://www.cpc.ncep.noaa.gov/data/indices/wksst9120.for.
According to NOAA’s CPC, SST anomalies equal to or greater than 0.5 °C in the Niño 3.4 Region are indicative of ENSO warm phase (El Niño) conditions, while anomalies less than or equal to −0.5 °C are associated with cool phase (La Niña) conditions³². Super El Niño events are typically defined by SST anomalies of at least 2 °C in the Niño 3.4 Region^30,31.
The expected CO₂ emissions (ΔCO₂) resulting from the next Super El Niño event were estimated using the following equation:
where PV_Energy represents the annual PV energy generation, CO_2-intesity is the carbon intensity of electricity generation, and ΔPV_POT is the expected impact of the next Super El Niño event on PV potential in the country or region of interest. This estimation assumes that the energy shortfall caused by El Niño will be compensated using a mix of backup energy sources available in the country or region of interest, rather than relying exclusively on carbon-intensive power plants (e.g., coal power plants). In other words, for substantial but still moderate ENSO-driven deviations in solar generation (typically within ±10%), we assume most power systems compensate by proportionally increasing the dispatch of the available backup-energy mix. While the exact relationship between solar deficits and emissions may deviate from the strict linearity assumed in Eq. (4) under certain system configurations, we argue that such deviations will lead to uncertainties likely smaller than those introduced by the rapidly evolving energy mix itself.
Evaluating Eq. (4) requires accounting for significant sources of uncertainty. For instance, while a Super El Niño event may occur at any point within the next decade, the exact timing remains unknown. Additionally, the future values of PV_Energy, CO_2-intesity, and ΔPV_POT at the time of the event are uncertain. To account for these uncertainties, Monte Carlo simulations^72,73 were conducted for each country or region of interest.
To estimate the expected impact on CO₂ emissions if a Super El Niño event occurs within the next decade, we recursively applied Eq. (4) using large sets of previously generated values for PV_Energy, CO_2-intesity, and ΔPV_POT.
For PV_Energy and CO_2-intesity, values were randomly generated within the range defined by observed data from 2023 and projections for 2035 (Tables S1 and S2, respectively). While the former represents a worst-case scenario (with no progress over the next decade), the latter represents a best-case scenario, with PV generation estimates derived from the REMIND_EU 2.0 model, assuming the optimistic NewPl_1.5 scenario³, and carbon intensity values based on announced pledges and net-zero scenarios⁵⁸.
For ΔPV_POT, values were randomly generated within the range defined by the maximum and minimum 12-month average PV_POT anomalies observed during past Super El Niño events (Tables S3 and S4). Positive anomalies indicate PV power surpluses (i.e., energy oversupply), while negative anomalies signal PV deficits (i.e., energy undersupply).
The randomly generated values were then used as inputs in Eq. (4). Simulation results for some key regions with high PV penetration (and where the influence of El Niño is well established) are shown in Fig. S11. Results for other regions and countries of potential interest are summarized in Table S5. Note that our projections for the expected impacts of the next Super El Niño event already account for an exceptionally wide range of possible future backup-energy mixes (Tables S1 and S2). The effect introduced by these possible future energy mixes is presumably much larger than any arising from residual non-linearities in our simplified linear model (Eq. 4).
We conducted Pearson correlation tests to evaluate the dependence between SST anomalies in the Niño regions and selected variables of interest (PV_POT, for example). A low p-value (lower than 0.05) indicates statistical significance, suggesting a dependent relationship between the two time series. The tests were conducted using both annual averages and seasonal averages, with the latter based on meteorological seasons: DJF, MAM, JJA, and SON. For correlation maps, regions with statistically significant correlations are highlighted with stippling.
We used the two-sided Welch’s t-test to assess the significance of PV_POT anomalies during the Super El Niño events (1982–1983, 1997–1998, and 2015–2016), relative to the 1982–2024 period. The two-sided Welch’s t-test is a variation of the Student’s t-test, but it is more reliable when the two samples have different variances and/or unequal sample sizes. The tests were conducted using both 12-month averages and seasonal averages, with the latter based on meteorological seasons: DJF, MAM, JJA, and SON. Regions with statistically significant anomalies in Figs. 4a and S10 are highlighted with stippling.
As EU countries, we considered in this study Austria, Belgium, Bulgaria, Croatia, Cyprus, Czechia, Denmark, Estonia, Finland, France, Germany, Greece, Hungary, Ireland, Italy, Latvia, Lithuania, Luxembourg, Malta, the Netherlands, Poland, Portugal, Romania, Slovakia, Slovenia, Spain, and Sweden.
In this study, East China includes the provinces of Anhui, Fujian, Guangdong, Guizhou, Hainan, Hebei, Heilongjiang, Henan, Hubei, Hunan, Jiangsu, Jiangxi, Jilin, Liaoning, Shandong, Shanxi, Yunnan, and Zhejiang; the autonomous region of Guangxi Zhuang; and the direct-controlled municipalities of Beijing, Chongqing, Shanghai, and Tianjin.
SST anomalies in the Niño regions come from the Climate Prediction Center (CPC)⁷⁴ available at https://www.cpc.ncep.noaa.gov/data/indices/wksst9120.for. Data on PV capacity in plot (1a) (upper panel) are from the International Renewable Energy Agency (IRENA) renewable capacity statistics², available at: https://www.irena.org/Publications/2024/Mar/Renewable-capacity-statistics-2024. Data on PV power plants in plots (1a) (lower panel) and (1b) are from the Global Energy Monitor⁷⁵, available at: https://globalenergymonitor.org/projects/global-solar-power-tracker/. PV generation and carbon intensity of electricity generation in selected regions and countries for 2023 (Table S1) come from Ember´s Yearly Electricity Data (https://ember-energy.org/data/yearly-electricity-data/). In the case of China, provincial-scale PV generation was calculated by multiplying the installed PV capacity per province and the corresponding capacity factor. While the latter comes from He & Kammen⁷⁶, the former was quoted from the Chinese National Energy Administration (https://www.nea.gov.cn/2024-02/28/c_1310765696.htm). Expected changes in the carbon intensity of electricity generation in selected regions and countries over the coming decades (Table S2) are based on announced pledges and net-zero scenarios. Data for China, the EU, the USA, and India are sourced from the IEA⁵⁸ available at https://www.iea.org/data-and-statistics/charts/carbon-intensity-of-electricity-generation-in-selected-regions-in-the-announced-pledges-and-net-zero-scenarios-2000-2040. Estimates for France, South Korea, Italy, Australia, Spain, Brazil, Chile, Argentina, Germany, and Japan assume pathways similar to those expected in the EU. All of these countries have pledged to achieve carbon neutrality by 2050 or earlier. PV generation estimates for 2030 to 2050 (Table S2) for China, the EU, the USA, India, Japan, Germany, and France are derived from the REMIND_EU 2.0 model, assuming the optimistic NewPl_1.5scenario³. Projections for South Korea, Italy, Australia, Spain, Chile, Argentina, and Brazil assume growth pathways similar to those expected in the EU. Like the others, these countries have pledged to achieve carbon neutrality by 2050 or earlier. PV_POT data were calculated using atmospheric data from the ERA5 reanalysis dataset⁷⁷. Atmospheric data (including near-surface (2-m) temperature, wind speed, and the surface SW irradiance) come from the atmospheric reanalysis ERA5, produced by the European Center for Medium-range Weather Forecasts (ECMWF)⁷⁷. ERA5 data are available at: https://www.ecmwf.int/en/forecasts/datasets/reanalysis-datasets/era5.
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The support of FONDECYT 1231904 and USACH DICYT Vicerrectoría de Investigación, Desarrollo e Innovación is gratefully acknowledged.
University of Groningen, Leeuwarden, The Netherlands
Sarah Feron, Richard Bintanja & Anne Beaulieu
Universidad de Santiago de Chile, Santiago, Chile
Raúl R. Cordero & Jaime Pizarro
Japan Agency for Marine-Earth Science and Technology (JAMSTEC), Yokohama, Kanagawa, Japan
Alessandro Damiani
Integrated Research on Energy, Environment and Society (IREES), Energy and Sustainability Research Institute Groningen (ESRIG), University of Groningen, Groningen, the Netherlands
Paul Upham & Xin Sun
Royal Netherlands Meteorological Institute (KNMI), Department of Weather and Climate Modelling (RDWK), De Bilt, The Netherlands
Richard Bintanja
School of Meteorology, University of Oklahoma, Norman, OK, USA
Chenghao Wang
Department of Geography and Environmental Sustainability, University of Oklahoma, Norman, OK, USA
Chenghao Wang
College of Forestry, Wildlife and Environment, Auburn University, Auburn, AL, USA
Zutao Ouyang
Global Adaptation Center (GCA), Rotterdam, The Netherlands
Xun Sun
Department of Earth System Science, Stanford University, Stanford, CA, USA
Robert B. Jackson
Woods Institute for the Environment and Precourt Institute for Energy, Stanford University, Stanford, CA, USA
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S.F., R.R.C., A.D., P.U., R.B., X.S., J.P., C.W., Z.O., Xu. S., A.B., and R.B.J. wrote the text. R.R.C. and S.F. contributed materials. S.F., R.R.C., A.D., and Xu S. analyzed the data. All authors reviewed the paper.
Correspondence to Raúl R. Cordero.
The authors declare no competing interests.
This research did not involve human participants or animal subjects. Ethical approval was therefore not required. The authors support inclusive, collaborative, and reproducible research practices.
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Indonesia’s PLN has launched a tender for a 1,225 MW solar project that will be spread across several regions of the country. The state-owned utility has not publicly announced a closing date.
Image: mz romadhoni/Unsplash
Indonesian state-owned electric utility company PLN has opened a tender for a solar project with a total capacity of 1,225 MW.
The Mentari Nusantara I solar power project will be developed across multiple regions of Indonesia, with 35 MW planned in Sumatra, 340 MW in Kalimantan, 600 MW in Java, 50 MW in Sulawesi, 80 MW in West Nusa Tenggara and 120 MW in Maluku and Papua.
The tender is being run through an integrated procurement scheme titled ‘Giga One’, which the utility explains promotes economies of scale and provides measurable project certainty for investors by bundling several projects into one package.
PLN kicked off the tender process last week (April 30). The utility has not yet published a closing date for the tender but has given the projects a targeted commercial operation date of 2029.
Suroso Isnandar, Director of Project Management and New and Renewable Energy at PLN, said the Mentari Nusantra project is a key initial driver in supporting the Indonesian government’s target of building 100 GW of solar.
Isnandar also said Giga One is “a new blueprint for renewable energy procurement in Indonesia and an important milestone in the national energy transition journey,” while advising that the procurement strategy will be replicated in future hydropower, wind power and battery energy storage system tenders.
Earlier this year, the Institute for Essential Services Reform and Indonesia’s Coordinating Ministry for Economic Affairs published a study exploring how Indonesia can work towards its 100 GW solar target, which targets 80 GW of decentralised, small-scale solar systems alongside 20 GW of centralised solar.
Indonesia surpassed 1 GW of solar capacity last year, with total capacity reaching 1.49 GW.
From pv magazine Gobal
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MNRE has updated the ALMM List-I, adding 20 GW of solar module capacity in May 2026, taking the total enlisted capacity to 193,144 MW. Sudarshan Saur Shakti, Nav-Yug Solar and Silver Pumps and Motors are the new entrants. Waaree, Reliance Industries, Novasys Greenergy, Rayzon Solar, Luminous, PIXON Green Energy, Redren Energy have increased capacities.
May 04, 2026. By Mrinmoy Dey

Mufin Green Finance's Gunjan Jain Bets on Premium Financing as India’s Next Credit Opportunity

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Energy Security Has Evolved into a Strategic Imperative for India: Hartek Singh

Geopolitics Reshaping Solar Strategy, Says Hindustan Power's Chairman Ratul Puri

Solar Shifts Farming from Constraint to Opportunity, Says Solarsure’s Bhavesh Patidar

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Japan’s Bold Lunar Ring Plan Would Turn the Moon into a 24/7 Power Station  HotHardware
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A German research team has developed a nondestructive, on-site method to quantify water ingress in photovoltaic modules using near-infrared absorption (NIRA) spectroscopy calibrated with Karl–Fischer titration (KFT). The approach enables precise measurement of absolute moisture content in sealed modules without disassembly, improving inspection, failure analysis, and lifetime prediction.
Image: Fraunhofer Center for Silicon Photovoltaics (CSP), Progress in Photovoltaics: Research and Applications, CC BY 4.0

A German research group has developed a novel, nondestructive method to quantify water ingress in solar modules on site. The technique uses near-infrared absorption (NIRA) spectroscopy calibrated against absolute water content measured via Karl–Fischer titration (KFT), enabling inspectors to determine moisture levels inside modules without opening them.
“The methodology is noninvasive, requires no bill-of-material modifications such as additional sensors, and is broadly applicable to field-deployed modules, provided prior calibration has been conducted,” corresponding author Anton Mordvinkin told pv magazine. “Unlike conventional approaches, it does not rely on assumptions such as Henry’s law or on approximations of evolving barrier properties or uncertainties related to a module’s internal microclimate.”
Mordvinkin said the approach lays the groundwork for more precise modeling of moisture ingress and improves the reliability of module lifetime predictions. “It provides actionable insights for manufacturers to optimize the design and qualification of products resistant to moisture-induced degradation mechanisms, including moisture-induced degradation (MID) and potential-induced degradation (PID), particularly in challenging environments such as floating PV systems and tropical climates, as well as for emerging technologies like tandem cells,” he added.
He also noted that the method enhances solar park inspection by enabling the identification of modules with insulation deficiencies, supporting targeted mitigation measures. “These advances contribute directly to improved asset bankability and provide a robust technical basis for future warranty and reclamation processes,” he said.
Image: Fraunhofer Center for Silicon Photovoltaics (CSP), Progress in Photovoltaics: Research and Applications, CC BY 4.0

The novel method involves exposing polymer materials commonly used in PV modules to varying moisture levels through damp-heat testing. Each sample is then measured using near-infrared absorption (NIRA) spectroscopy, in which water is detected by its strong absorption of infrared light. However, as NIRA provides only a relative signal, the same samples are subsequently analyzed using Karl–Fischer titration (KFT), a technique that heats the material and precisely quantifies the amount of water released. By correlating the NIRA signal with the absolute water content determined by KFT, the researchers establish calibration curves for each material.
The materials tested include encapsulants such as ethylene-vinyl acetate (EVA), polyolefin elastomer (POE), thermoplastic polyolefin (TPO), and thermoplastic polyurethane (TPU), as well as backsheets such as polyethylene terephthalate (PET), polypropylene (PP), polyamide-aluminum-polyamide (AAA), polyvinylidene fluoride (PVDF), and fluorinated-coated PET.
Image: Fraunhofer Center for Silicon Photovoltaics (CSP), Progress in Photovoltaics: Research and Applications, CC BY 4.0

Once calibrated, a handheld NIRA spectroscopy device can be used directly on installed the modules. To demonstrate this capability, the research team tested minimodules with PET- and PP-based backsheets under damp-heat conditions, polymer coupons exposed to accelerated ultraviolet (UV) radiation and humidity aging, rooftop modules exhibiting backsheet cracking and snail trails, and field-retrieved modules with both cracked and intact AAA backsheets to compare real-world moisture ingress and degradation behavior.
The tests showed that PET-based modules absorbed more water than PP-based modules. In field studies, modules with backsheet and cell cracking exhibited up to 50% higher water content, while modules with cracked AAA backsheets absorbed water up to ten times faster than intact reference modules.
“In this work, it was found that the improved barrier performance of PP is primarily governed by its lower water solubility, whereas the diffusion coefficients of both materials are comparable,” said Mordvinkin. “This provides a more detailed mechanistic explanation for the previously observed differences and is consistent with trends reported in the literature.”
“Another particularly insightful observation is the presence of a non-homogeneous water-content distribution in modules with severely degraded backsheets after extended outdoor exposure of over 7 years,” he added. “Localized moisture accumulation was significantly enhanced in regions with cell microcracks, which correlate with visually observable snail trail patterns. This finding points to a coupling between mechanical degradation and localized moisture ingress behavior.”
The new method was presented in “Nondestructive Quantification of Water Ingress in PV Modules via Spectroscopic and Chemical Analysis for Enhanced Quality Assurance and On-Site Inspection,” published in Progress in Photovoltaics: Research and Applications. Researchers from Germany’s Fraunhofer Center for Silicon Photovoltaics (CSP), Fraunhofer Institute for Microstructure and Systems (IMWS), and Forschungszentrum Jülich have contributed to the study.
This content is protected by copyright and may not be reused. If you want to cooperate with us and would like to reuse some of our content, please contact: editors@pv-magazine.com.
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Engie Brasil to back three innovation projects for solar PV plant solutions  Renewables Now
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Brazil’s Aneel has revoked 3.57 GW of photovoltaic project authorizations across four resolutions, mainly at the request of developers citing insufficient grid evacuation capacity and rising curtailment.
Image: Ilanwet, Pixabay
From pv magazine Brazil
Through four resolutions published in recent days, Brazil’s National Electric Energy Agency (Aneel) revoked authorization for photovoltaic projects totaling 3,572 MW. The cancellations were requested by the project developers themselves, with the most frequent justification being insufficient grid evacuation capacity to connect plants to the transmission and distribution system. Generation curtailment was also cited.
Auren relinquished the largest volume of projects among the revocations published last week. Other companies, including Solatio and Enel Green Power, also requested the cancellation of more than 500 MW each.
By state, Piauí and Minas Gerais account for most of the revoked capacity, with 1,747 MW and 1,265 MW, respectively. Additional projects were cancelled in Bahia, Tocantins, and Rio Grande do Norte.
To qualify for revocation, projects must not have sold energy in the regulated market, meaning the authorizations applied to projects intended for the free market.
Despite recurring cancellations – another 2.8 GW were revoked in March – solar remains the leading technology in Brazil’s utility-scale expansion pipeline. Aneel’s tracking system, Ralie, currently lists 79 GW of projects at different stages of development, followed by 14.7 GW of wind capacity.
Distributed generation is also facing similar grid connection constraints. Alongside transmission expansion through auctions, increased battery storage deployment is being considered as a potential solution to alleviate bottlenecks.

Longroad starts operations at Sun Pond solar-BESS plant in Arizona  Renewables Now
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Efficiency enhancement of solar PV panel by incorporating wickless loop heat pipes with plate type evaporator  nature.com
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The influence of solar PV panels on CO dispersion in ideal 2D street canyons  nature.com
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The full potential solar photovoltaic (PV) energy is not utilised by the mining industry due to heavy dust deposition and harsh operating condition. This study aims to quantify the seasonal impact of dust deposition on PV performance and determine the optimal cleaning frequency for optimize the performance of solar PV Panel in an operational mining condition. Additionally, an innovative automated dry dust cleaning system is designed, developed, and validated in the active mining field to evaluate its operational efficiency and durability. A comprehensive study of twenty-six week was conducted to monitor the variations in dust deposition density and output energy of PV panel across three distinct seasonal phases. Among these, pre-summer phase showed the highest dust deposition density of 5.98 g/m² and due to this maximum output power (P_max) of dusty panel reduce by 63.50%. This phase experienced an intense mining activity and dry weather condition. Therefore, a cleaning schedule of 3 to 4 days is recommended to effectively utilise the potential of PV panel. The other two phases such as dry winter and early monsoon experienced comparatively lower average reduction of 35% to 40% in maximum output power. A moderate cleaning scheduled of 6 to 7 day is recommended for these two phases Further, the developed dust cleaning system is validated in the mining field under three different environmental phases and an average recovery of 40% in Pmax is obtained across three phases. This presents the effectiveness of developed dust cleaning system under real operating condition. The outcome of this research highlights the need of dynamic cleaning schedule for effective utilisation of solar energy in mining industry. The integration of smart dust sensors and AI based predictive modelling of developed cleaning system for sustainable utilisation of solar energy in mining and allied industries.
The mining industry is the backbone of the country economy that includes energy intensive operations. These operations receive energy from conventional grid and diesel operative power generation which is not a sustainable solution. Therefore, there is an urgent need for sustainable energy solutions for powering the operation of mining industry. Solar PV panels emerges as a alternative solution that only full-fill the energy demand of mining industry but also reduces its carbon foot print^1,2. Solar based power solution enables the mining operations to meet global decarbonization goals. The effective integration of solar energy in the mining industry supports would be able to full-fill all its energy demand. This not only promotes green mining initiative but also provides a decentralised uninterrupted mining operation. As a result, efficiency of mining industry can be increased while maintain its commitment towards sustainable growth. The introduction of solar PV based energy emits zero emission during its operation and lowers long-term costs^3,4. The full potential of solar PV energy can not be utilised due dusty and harsh operating condition. Mining industries generally located in remote locations which experienced a seasonal variation, higher dust generation and dynamic operating conditions^5,6,7. These operational parameters reduce PV panel performance significantly mainly due to the deposition of thick dusty layers which is produces due to heavy machinery operations. This demotivates the deployment of solar PV system in mining industry. This deployment issue is not just a technical challenge but is also logistically complex^5,6. Therefore, for smooth operations there is a need of strategic planning which can tackle dust deposition problem and improves the performance of solar panel under high dusty locations^6,8,9.
Mining industry is one of the challenging sites for effective utilisation of solar PV energy. This is mainly due to its harsh climates, extreme temperatures, and dust surroundings. These issues are the main obstacles for the effective deployment of solar PV systems. Mining industry produces higher rate of dust pollutants than any other industry. Dust play a major role in reducing the PV panel performance thus managing the dust deposition can optimise the panel performance in mining environment. In mining industry, the continuous operation of heavy machinery and constant excavation activities such as drilling, blasting, and hauling exacerbate dust generation that leads to higher deposition over the panel surface¹⁰. This can cause short-term energy loss and long-term damage to the surface of PV panels. The excess generation of dust reduces the optical transmittance of panel glass consequently lowers generation of electric charges form PV panel. This reduces the performance of solar PV panel in harsh dusty condition which indicates more cleaning operation that increase the maintenance costs and reduce the life span of the solar panels^{11,12,13,14,15}. Thus, an effective dust control measures can improves the panel performance which allows the panel to operate in its full potential.
Previous studies reported a significant performance degradation of solar PV panel in dry and dusty industrial zones. One study reports the reduction of 20% to 60% in output power of solar PV panel¹⁶. The variation of performance degradation under dusty environment depends on dust type, location, and panel installation angle. Previous studies present various predictive model of solar PV performance against different operating parameters namely dust density, solar radiation, temperature, and humidity. The operating parameters like solar radiation, temperature and humidity affect the dust deposition density over the panel surface. The performance predictive model provides useful insights and environmental sensitivities that promotes the effective utilisation of solar energy in mining industry. Most of these models are simulation-based and lack of data validation. Thus a comprehensive study of panel performance under real mining condition needs to be performed^{17,18,19,20,21}.
Mining industry shifting its energy dependency from fossil to non-fossil fuels based energy sources like solar PV. In recent time, huge capacity of solar PV is installed in various coal and metal mines in the country. These installed panels continuously experiencing the drop in its performance. Dust accumulation is major reason for reducing panel performance under high dusty condition of mining industry. This needs a frequent dust removal maintenance which increases the cost of operation. Therefore, it is necessary to optimize its cleaning cycle that enhance its performance under high dusty environment. Although several cleaning approaches like manual, semi-automatic, and robotic have been developed but most of these are optimized for urban or residential contexts. Very limited studies address this unique challenges under harsh mining conditions. A mining industry provides a dynamic operating condition through continuous excavation, hauling, and crushing activities. These activities generate significant amount of dust that creates a adhesive dust layers over the panels surface. Mining dust differs from typical environmental particulates: it is coarser, more metallic, and forms a persistent film that resists conventional cleaning. If these layers are not cleaned at regular intervals, they may form permanent dark spots on the panel surface. This not only reduces the PV panel’s performance but also shortens its operational lifespan. Presently, water-based cleaning is more popular in mining areas which is not a sustainable cleaning solution. Therefore, there is a need to develop an alternative approach of cleaning the panel surface so that its performance can be improved under dusty condition. Further, there is a need to determine the optimum cleaning time for mining industry because under and over cleaning disturb the operating efficiency of PV panel. Moreover, earlier studies predominantly relied on controlled laboratory tests or static setups that do not reflect the real dynamics of mining environments. Therefore, it is essential to examine in situ PV performance under actual field conditions using innovative cleaning techniques and to determine optimized cleaning intervals. These two aspects are critical for improving energy yield and maintenance planning in industrial solar energy systems.
To bridge the existing knowledge gap, this study introduces a novel field-based framework for determining the optimized cleaning interval of solar PV panels operating under mining dust exposure. This study aims to design and implementation of an automated dust cleaning system that enable periodic removal of deposited particulates from PV panel surface. The designed cleaning system is validated under real operating mechanized iron mines which is located in the southern India. A detail field investigation is performed to evaluate the efficiency of solar PV panel that address the impact of dust deposition and optimize cleaning frequency on the panel performance. The key electrical parameters such as short-circuit current (Isc), open-circuit voltage (Voc), and maximum power output (Pmax) were considered during analysing the panel performance under dusty condition. This study establishing a direct link between automated cleaning efficiency and real-world performance recovery of solar PV panel under challenging mining condition. A developed dust cleaning system offers a cost-effective, waterless, and no human indentation which is specifically engineered for harsh mining environments. By combining field-scale validation and optimise cleaning frequency addresses scientifically rigorous and practically scalable framework for enhancing the performance, reliability, and sustainability of solar PV systems in dust-intensive mining operations.
Rapid industrialization and urbanization are the main cause of airborne dust pollutants²². These particles settled on the panel surface and create a thick layer of dust deposition that attenuates a significant amount of sun light to penetrate the glass surface^23,24. The degree of this attenuation depends on several factors, including the size, density, and type of dust particles. Finer dust particles can diffuse sunlight more effectively, while larger or denser dust clusters block sunlight directly^25,26. As a result optical transmittance of panel glass reduces under the high deposition of dust over its surface. Thus, the performance of solar PV Panel often degrades considerably in dusty and industrialized areas^27,28,29. Mining industry is considered as one of the highest contributors of air pollution. Due to higher generation of dust solar PV panel does not perform at its full potential. This layer of dust attenuates incoming sunlight, significantly reducing energy conversion efficiency. Type of dust deposition also affect the performance degradation. One study recorded the reduction in solar PV energy of 19%, 10%, and 6% for the deposition of red soil, limestone and ash respectively³⁰. In one of the study deposition of ash dust over the panel surface showed more reduction in its performance when compared to other deposited pollutants like red soil, sand, calcium carbonate, and silica gel. The study reported the minimum reduction of 0.9 V to maximum reduction of 4.7 V in output voltage of PV panel due to different deposited dust pollutant³¹. Further, a same level of dust deposition offers the different performance degradation for two different technologies of solar PV panel. A study demonstrated the different in monocrystalline PV panel showed lesser performance degradation than multi-crystalline under same level of dust deposition density. This is mainly due to the quality of silicon that decides the panel performance under expose environmental conditions³². A study showed the lesser reduction of 4.1% in short circuit current of monocrystalline panel compared to 4.79% and 7.34% for polycrystalline and amorphous silicon respectively³³.
To effectively utilise the potential of solar PV panel there is a need of robust dust cleaning techniques particularly when panel installed around high-dust zones like mining industries. In recent time, different cleaning techniques are reported to over the problem of dust deposition over the panel surface. Water based cleaning mix with detergent is the most common practice for cleaning PV surface for small scale installation³⁴. This methods not suits for large scale industrial installation due to its high demand of water and manual intervention. Thus, it not a feasible dust cleaning solution for arid and mining regions where water availability is limited. Additionally, the more usage of detergent chemically impact the optical properties of the glass by leaving chemical residue on its structure. Due to this physical structure of panel degrades at faster rate that reduces its end of life (EoL)^35,36. Moreover, manual cleaning introduces operational downtime and safety risks for maintenance personnel, especially in elevated or hard-to-reach installations. The water cleaning technology disturb the panel performance by promoting micro-cracking due to thermal shock during rapid interaction of cold water with hot panel surfaces. The frequent application of the water on the panel glass degrades its mechanical strength. Thus, this method is not a feasible solution for larger installations. For larger installations, high-pressure water jets in combination with brushing have been reported an effective cleaning method. This study noted a significant improves the panel performance when compared to traditional water-based cleaning. in output power following such cleaning regimes^37,38,39. One study demonstrated that manual cleaning with a water brush system led to a significant increase in output power for a PV plant, offering a unique solution to the advancement of solar PV systems^40,41. However, these methods are not cost effective solution as it need a labour intensive job. This may provide an impractical solution in remote or water-scarce environments which is general scenario in many mining regions. Further, the application of high-pressure water jet may damage the glass integrity consequently its optical properties gets reduce. Therefore, there is a need of innovative cleaning technology that provides more feasible and environmentally friendly approach. A good cleaning system is one which provide minimal environmental footprint and reduced maintenance effort to optimise the panel performance.
Electrostatic dust cleaning is one of the innovative approaches for promoting dry cleaning that uses a series of alternating electrodes. These electrodes are embedded in a transparent dielectric film on the panel surface that charged the dust particles. These charged dust particles repel each other that supports the removal of dust deposition form the panel surface. This offers a solution that clean the panel surface without water and any moving parts^42,43. But this technology suffers with its low dust removal rate that makes it a least effective under dusty operating environment. Further, due to rapid advancement of electronic components and accessories automatic operations becomes more popular. Automatic cleaning system provides a viable environment friendly approach to recover the performance of dusty solar PV panels. These systems typically use computer-controlled mechanical devices to automate the surface cleaning operation and are considered more efficient and reliable than manual methods. The automated dust cleaning system reduces labour and water consumption costs this makes it more suitable for large scale installation. A study conducted by Tejwani and Solanki (2010) showed an improvement of 15% in output power of dusty panel due to the integration of automatic dust cleaning system⁴⁴.
Earlier studies on automated and electrostatic cleaning systems showed promise for performance recovery. However, most were done in controlled labs or small residential-scale conditions. These systems usually assume that dust is uniform, conditions are stable, and there is little mechanical stress. But these assumptions often fail in mining environments. In mines, dust is highly heterogeneous, abrasive, and dynamically deposited due to excavation and haulage activities. This makes most of the earlier designs unsuitable for long-term deployment. Furthermore, prior works rarely examined the optimization of cleaning frequency^45,46. The optimize cleaning is an important parameter that affect the cost of cleaning system. Due to dynamic and harsh operating environment there is a need of conducting scientific study that can able to address the proper cleaning cycle. This technique results in lowering the excessive energy consumption and minimizing inefficient cleaning schedules. As the technology is enhancing there is potential of implementing robust sensor based cleaning mechanism that can able to operate in synchronous manner with reference to its cleaning cycle⁴⁷.
Despite the advances cleaning technologies, limited attention has been given for determining the optimal cleaning frequency under real mining conditions. The determination of optimum cleaning is a necessary parameters as the dust generation is continuous and highly variable. Cleaning too frequently leads to unnecessary operational costs and energy use, while delayed cleaning results in severe performance degradation. Hence, defining an optimal interval is essential to balance efficiency, resource use, and maintenance effort. This analysis provides a site-specific optimized cleaning frequency that maintain the performance of solar PV under harsh operating environments like mining industry. To bridge this present study showed the seasonal performance degradation of solar PV panel in a mechanized iron mine located in southern India. The study highlight the effectiveness of automatic dust cleaning system that validated under real operating mining condition. The study provides the quotative degradation of panel performance under considered mining site that help in deciding the optimum cleaning time. This optimum cleaning mechanism not only improves the panel performance in long run but also improves the structural integrity. The field validation of developed sensor-assisted dry cleaning system highlights the effective utilisation of solar PV energy system in harsh operating mining conditions. It provides useful insights to improve solar energy use in tough industrial settings.
The study conducted in a mechanised surface iron ore mines located in Chitradurga District of Karnataka State with geographical coordinate of 14° 8’ 55.4928’’ N, 76° 40’ 1.1424’’ E. This site presents both favourable and unfavourable condition of effective utilisation of solar PV. The favourable operating condition offers high average solar radiation and good climatic condition throughout the year. In any sunny days a maximum solar radiation of 1120 W/m² can be recorded at ranging atmospheric temperatures from 25 °C to 37 °C and wind speeds peaking of 4 m/s. These environments offer a favourable operating condition for solar PV installation under any real field deployments. The continuous mining operations like drilling, blasting and hauling generates a significant dust deposition density over the panel surface which is considered as the unfavourable operating condition of solar PV under mechanised iron ore mines.
Map showing the geographic location of the study site where the field study was conducted. (Solar paper map was taken from Google – https://shorturl.at/c11td).
The mining industry includes heavy machinery operations, generates significant dust cloud in and around the mines that provide a challenging dynamic condition for optimizing the performance of solar PV Panel. After the blasting operation, a heavy excavator of capacity 6.5 m³ and 55 MT dumpers are used to transport the fragmented material. Two different drilling machines of 270HP and 380HP are used to create 150 mm diameter blastholes. Even though of usage of dust control measures like water injection and control drilling operations mining industry generates significant dust cloud that is sufficient to degrade the panel performance. Due to fast and dynamic dust condition this mining sites is well suited for study dust impact and its mitigation approach on solar PV panel performance. The site provides validates the effectiveness of developed automatic dust cleaning system under any harsh dusty environments. Figure 1 shows the geographic location of selected study site. From Fig. 1, the positioning of geological map within Karnataka State demonstrates the relevance of this study under the operating mining condition.
The performance of PV panel under dusty exposure is studied under real operating mining condition where no artificial or manual deposition was performed for assessing the panel performance. The purpose of this study is to assess the effeteness of developed cleaning system under real operating environment, and a site-specific cleaning system can be designed for different seasonal condition. During the study period daily measurements of weather data like temperature, humidity, and wind speed were recorded. These measurements help us to establish the link between dust deposition and environmental parameters. Though these variables cannot control but their analysis will help in developing an efficient dust cleaning system.
A twenty six week of field study is designed to investigate the dust of dust deposition on the performance of solar PV panel under operating condition of mechanized iron mines. Two identical polycrystalline solar panels kept side by side facing towards south near weighting bridge area of the selected mechanised mines. This arrangement help in comparing the panel performance of dusty and clean panel under same environmental conditions. One panel is designated as the “dusty panel,” which is left uncleaned during study period whereas other is designated as “clean panel” where daily cleaning is performed. This direct comparison between clean and dusty panel offers many insights that presents realistic dynamic challenge to operate the panel at its full potential.
The deposition of dust is measured by placing the filter paper of identical panel surface area adjacent to the clean panel. By doing the weight analysis of pre and post dust deposition in filter paper provides the daily variation of deposited dust over the panel surface that left undisturbed throughout the day. After every 24 h the filter paper removed and weighed using a high-precision (accuracy: ±0.001 g) digital weighting machine. The difference in pre and post deposition of dust mass is divided by the panel surface area which gives the deposition density in grams per square meter (g/m²). This process is repeated daily throughout the study period that enables a time-series record of dust deposition. The comprehensive time series analysis of 26-week provides a complete assessment of long-term trends of dust deposition and performance degradation under real mining conditions. Table 1 presents the weekly deposition of dust over the panel surface which is showing variations in daily accumulation due to operational and environmental factors. These variations are considered to determine the optimal cleaning frequency that indicates the point at which panel efficiency degrades if left uncleaned.
Table 1 indicates the progressive and seasonal impact of dust deposition over the panel surface from the January–June. It summarizes the weekly and total surface deposited dust densities. The data of Table 1 shows low deposition during winter months (January–February), gradually increasing during peak summer (May). From peak summer to early monsoon dust deposition again reducing that shows the lesser impact of dust in this phase. Therefore, the entire study period is divided into three different phases such as dry winter, summer and early monsoon. The trends of deposited dust densities over the panel surface confirm the need of dynamic shift in cleaning cycle due to variation in deposited dust particles. This variation also provides the alteration in the panel performance under diverse operating condition. This establishes a strong correlation between electrical output and dust deposition.
A two identical 20 W polycrystalline solar panel termed as clean and dusty used in this study is shown in Fig. 2. A weekly comparison between clean and dusty panel is used in assessing the optimum cleaning schedule for different weeks of study period. The comparison of clean and dusty panel is performed for total twenty six week of study period that enable the assessment of seasonal analysis of solar panel performance under harsh operating mining condition. The dynamic variations in operating seasons and mining activities demonstrates the need of dynamic cleaning schedule that operate at its optimum value. The technical specification of 20 W and 10 W (used in cleaning system design) solar panel is presented in Table 2. The key electrical parameters such as output power, current, and voltage were measured using a 320 Ω rheostat and two digital multimeters (one functioning as an ammeter and the other as a voltmeter). The collected electrical parameters is analysis to study the impact dust accumulation on solar panel performance. This experimental setup offered a comprehensive analysis of the performance degradation of solar panel caused by dust accumulation. This analysis provides the initial evidence to establish a correlation between dust deposition and solar panel efficiency. This preliminary understanding helps in determining the optimal cleaning frequency. This optimum cleaning subsequently supports the efficacy of the developed cleaning system for removing the dust particles form the panel surface.
Close-up view of the two identical 20 W polycrystalline solar panels used in the study.
Table 3 provides the detailed technical specifications of all measuring instruments used in this study. All instruments were pre-calibrated before field deployment as per manufacturer standards. To avoid atmospheric variability measurements were taken during clear sky conditions. The validation of developed dust cleaning system is performed on 10 W mono-crystalline PV panel and the performance of panel is recorded in post-cleaning operation under real mining dust exposure.
To mitigate the impact of dust on panel performance an automatic dry dust cleaning system is designed and implemented in real operating mining condition. This simulates the efficiency of developed dust cleaning system under harsh mining environments. The main purpose of designing this cleaning system is to minimise the need of human intervention and water consumption. This dry-cleaning system offers the best performance of installed solar panel in harsh mining environments. The field validation of developed cleaning system is performed with 10 W polycrystalline solar PV panel in peak dust deposition period. This small developed prototype allow the operational adjustments during field validation that gives a strong foundation for its larger installation area. This approach allowed a precise control on design process and facilitated adjustments as per dynamic operating condition.
The main consideration while designing the automatic cleaning system is to establish the effective coordination between mechanical and electrical components of cleaning system. This coordination is controlled by microcomputer assembly known as Arduino microcontroller. This is the main part of cleaning system which governs the entire cleaning process. This control the operation of motor driver circuit (L293D) that is direct the movements of DC gear motor. This facilitates the movements of wiper arrangements over the panel surface. The speed of wiper can be controlled by motor driver circuit that makes it more suitable to use over the panel surface under dynamic dusty condition. The wiper is freely mover across two ends of solar panel and removes the deposited dust from its surface. The wiper consists of a dry sponge material that effectively clears dust while minimizing friction over the surface that provides less damage to the glass integrity.
The dry sponge cleaning wiper provides lightweight that gives less mechanical stress on the panel glass during the cleaning operation. This help in developing an effective cleaning technique that removes significant dust from the panel surface. A 30-laboratory cleaning trial is performed over the panel surface and no surface damage is reported over the panel surface. These tests will help in defining the maintenance schedule and lifecycle analysis of the panel surface. The wiper is moved over the panel surface through the two endless belts which is positioned on either side of the panel. This belt is powered by the DC gear motor that rotate the belt that facilitate the top and bottom movement of the wiper over the panel surface. Wooden wheels support the belts and guide the wiper as it moves across the panel. When wiper is moved across the panel surface then its direction is controlled by the reversing the motor operation. This can be achieved using motor driver circuit which is connected with pin 26 and 28 of Arduino microcontroller as shown in Fig. 3. When wiper reaches at one end of the panel then it meets limit switches and activates it for providing smooth flow across the panel surface without risk of mechanical overload.
Circuit diagram of the proposed dust cleaning system.
Figure 3 presents the schematic circuit diagram of developed automatic dust cleaning system. A real the clock (RTC) triggers the Arduino microcontroller that initiate the cleaning dust system. The RTC give the activation pulse at predetermined intervals and entire cleaning system starts. Upon activation, the microcontroller sends the initiation pulse to the motor driver circuit that trigger the movement of wiper though belt rotation. The limit switches control the direction of wiper movement by sending reverse pulse to the motor driver circuit. The operational flow of this automated cleaning mechanism is further presented in Fig. 4.
The photographic view of developed dust cleaning system is shown in Fig. 5. Various operational components including the belts, motor, and wiper mechanism, are assembled onto a solar panel. The system is powered by a 12 V DC power supply that provides a stable and efficient energy source for continuous operation of cleaning system. Due to dry sponge characteristics of wiper panel dust not sticks with wiper surface that enables multiple cleaning cycles. This improves the effectiveness of developed dust cleaning system under harsh dusty condition. In the field every morning real-time clock (RTC) triggers the cleaning system for removing accumulated overnight dust from PV panel surface. The automatic cleaning system offers benefits to in remote or difficult-to-access areas where manual cleaning would be impractical.
Flowchart of the automatic dust cleaning system.
Developed dust cleaning mechanism.
The Algorithm 1 as mentioned in below section provides the complete operational logic of the developed dust cleaning system. The provided pseudocode presents the working of automatic dust cleaning system based on the constant cleaning interval and available motor logic. The pseudocode simulates cyclically nature of developed dust cleaning system that requires no manual intervention once programmed properly.
Operation logic of the automated dry-cleaning system.
The economic viability of the proposed automated cleaning system was evaluated by balancing energy yield recovery with system cost. The cleaning frequency was determined using the normalized power loss data from the field, which indicated that the highest performance degradation occurred in the first three days, followed by a more gradual decline. Cleaning every 3rd or 4th day showed to recover approximately 35–38% of lost energy, aligning with a practical cost-benefit threshold.
The cost breakdown included: Arduino microcontroller (₹500), motor driver and DC gear motor (₹700), RTC module and limit switches (₹400), sponge-based wiper and belts (₹300), and panel mounting frame (~₹500). The system operates on a 12 V DC power supply with negligible operational power draw (5–10 W/session). With total capital investment under ₹3,000 and considering average electricity rates of ₹7/kWh in India, the system pays for itself in under 6–7 months when deployed on larger PV arrays.
The long-term impact of dust deposition on solar PV performance is evaluated for a 26-week period ranging from January to June 2023. The study represents the feasibility of utilisation of solar energy in an operational mining condition. Here the focus is to optimize its performance by determining optimum cleaning cycle and validation of developed water less dust cleaning system. The main objective of this study was to capture the progressive degradation pattern under actual mining and seasonal conditions. Table 4 shows the readings obtained during the study which incorporates the values of average solar radiation, dust deposition density and electrical parameters for both clean and dusty panel. During the winter months (Weeks 1–8), dust accumulation ranged between 2.1 and 4.5 g/m², attributed to dry atmospheric conditions and moderate wind speeds (2–3 m/s). A pronounced increase occurred during the pre-summer phase (Weeks 9–17), when deposition peaked at 5.5 g/m². This time accompanied heavy mining work such as drilling, blasting, and hauling operations which is performed in dry windy weather. The early monsoon period (Weeks 18–26) exhibited less dust deposition due to rain and higher humidity, which helped clean the panel surface a bit.
During the initial phase of study in week-1 clean panel produced a maximum power output of 9.8 W when compared to 6.9 W of dusty panel. This indicates the reduction of nearly 30% in maximum output power whereas short-circuit current exhibited a sharper decline of 22.4%. The open circuit voltage shows slight reduction of 1.5%. This confirms that dust majorly affects the short circuit current and maximum power output as compared to open circuit voltage. This is mainly due to light scattering and absorption phenomena of dust deposition. Over time, this difference became more pronounced, as dust thickness increased and surface roughness enhanced light attenuation. By week-14, dust accumulation was highest. The power of the dusty panel dropped to 3.5 W. In contrast, the clean panel stayed at 9.6 W. This results in a 63.5% decrease in power generation.
A week 1 to 8 is the representation of winter months where dust accumulation ranged between 2.1 and 4.5 g/m². This attributed to dry atmospheric conditions and moderate wind speeds in the range of 2–3 m/s. During this period a progressive loss in optical transmittance was observed which reduces the electrical output of solar PV panel. During this phase, the average solar irradiance remained moderate (795–835 W/m²) allowing a consistent performance from clean solar panel ranging from 9.0 to 10.0 W. However, the dusty panel demonstrated a steady decline in maximum power (P_max) from 6.8 W in week 1 to 5.1 W in week 8. This highlights the degradation of PV panel performance approximately 25% for these two months. This early trend confirmed that the dust layer primarily obstructed light penetration rather than altering cell junction properties.
The pre-summer phase from weeks 9 to 17 witnessed an increase amount of dust deposition ranging from 4.0 to 5.5 g/m². This increased deposition happening together with intensified mining operations under dry and windy conditions. The average solar irradiance increased moderately from 800 to 925 W/m². Even though, this phase provides higher amount of solar irradiance but panel does not perform well due to more dust deposition density in this phase. This higher dust deposition density reduces the panel performance due to the thick layering of dust over the panel surface. It shows a significant impact of dust on solar panel performance under favourable operating condition. In this phase, a maximum reduction of 63.54% for P_max of solar panel is observed. This indicates a considerable degradation in the panel performance due to high exposure of dust. As shown from Table 4, dust accumulation reached its seasonal peak in week 14 due to the influence of peak dry season, intensified mining operations, and strong re-suspension winds. In this week, output power of dust panel dropped to 3.5 W while the clean panel maintained around 9.6 W. This results a reduction of 63.5% loss in power generation of solar PV panel as shown in Fig. 6. This is the peak in which highest reduction in solar power generation reported even due to the highest accumulation of 5.98 g/m² dust density as shown in Fig. 7. Week 26 indicates the lowest deposition density of 2.20 g/m² with the reduction of 29.70% in P_max. This is mainly due to the higher solar radiation of 940 W/m² when compared to 780 W/m² of week 14. Further the panel surface and partial removal or redistribution of loosely bound dust particles caused by pre-monsoon humidity and mild rainfall events, which reduced the effective shading on the PV cells. During this period, the dusty panel’s I_sc dropped below 0.36 A, and its Voc decreased by approximately 0.8 V relative to the clean panel. This reflects partial hindrance of photon absorption and charge carrier generation, as also supported by visual observation of fine, clay-rich particulate layers forming non-uniform coatings and inducing localized micro-hotspots.
Weekly reduction in maximum power output of dusty PV panel throughout the study.
Study week 18 to 26 presents the starting of early monsoon period and during this period dust deposition gradually reduced. This is mainly due to the occasional rainfall, higher humidity, and reduced airborne dust concentration. The average deposition density decreased from 4.35 g/m² in week 18 to 2.20 g/m² in week 26. This study duration shows the higher solar radiation correspondingly. The higher radiation week offers a slower reduction in maximum power output power, thus less frequency cleaning can be used in these seasons. This will reduce the cleaning cost and power that require to clean the dusty PV panel. The optimization of cleaning cycle can be be performed based on the dust deposition rate and this can be achieved systematically using fully automated dust cleaning system.
Weekly reduction dust deposition density on panel surface throughout the study.
Overall, the six-month performance trend demonstrates that dust accumulation causes a nonlinear but progressive decline in PV output, primarily by reducing the short-circuit current and maximum power output which can be seen from Figs. 8 and 9. The open-circuit voltage remains relatively stable throughout the study when compared to the short circuit current of the panel. This signifying that surface dust mainly influences optical transmittance rather than internal cell dynamics. The magnitude of performance loss was directly linked to dust load intensity and particle morphology, both of which varied seasonally due to changing meteorological conditions and mining operations. As shown in Fig. 8, short-circuit current exhibited a similar trend like maximum power output where the maximum reduction happened in the week 14. The short circuit current reduces from 0.67 amp (for clean panel) to 0.31 amp (for dusty panel). Dusty panel showed the highest value of 0.54 amp in week 26 whereas clean panel showed the value of 0.70 amp. The sharp early decline and partial later recovery illustrate that current output is the most sensitive electrical indicator of dust interference. Figure 9 presents the variation of open-circuit voltage (Voc) where the lowest value of 19.30 amp was observed. The variation of open circuit voltage least affected by the dust deposition as it logarithmically depended on the solar radiation. This slower decay supports prior findings by Fatima et al. (2014), which suggest that voltage is less sensitive to low-level shading but responds when coverage becomes extensive or non-uniform. Even then, minor voltage degradation contributes cumulatively to overall performance loss¹². In the similar manner, the study in¹³ shows the dust buildup can reduce PV output by 50% in tropical areas under high exposure of dusty cloud.
This study presents a non-linear degradation pattern of solar panel performance under dynamic condition of mining industry. Initially a rapid decline then saturation at peak dust load (during 14th week), and partial recovery thereafter is noticed in the performance of PV panel. This highlights a dynamic cleaning schedule based on the seasonal variation of dust deposition density over the panel surface. These findings supports the flexible and site-specific maintenance strategies rather than fixed cleaning intervals for effective utilisation of solar PV panel in mining industry.
Weekly variation of short-circuit current for clean and dusty panels throughout the study.
Weekly variation of open-circuit voltage for clean and dusty panels throughout the study.
The finding of our study also supported by Elamim et al. (2024) where power output dropped by 20–60% in Mediterranean climates¹⁶. This change depended on the exposure period and the type of dust involved in the study. Similarly, Kazem et al. (2022) observed a 36% drop in PV output over 10 days in a desert region of Oman, primarily due to fine sand particles and dry air conditions¹⁹.
Our study found a maximum drop in output power at a mechanized iron mines when relatively compared with previous study. This happened even though the exposure times were similar or shorter. This stronger degradation is due to some special characteristic of mining industries:
High particulate density: Excavation, drilling, hauling, and blasting produce much airborne dust. This includes coarse mineral dust that quickly settles on panel surfaces.
Heavy dust adhesion: Mining dust has metallic oxides, clay fines, and silica particles. These stick more than sand or urban dust. This is due to electrostatic effects and moisture from machines.
Proximity to source: In our study, the panels were within 15 m of active haul roads and crushing zones. This closeness meant they faced constant soiling, with no natural or structural barriers to protect them.
Surface abrasion and micro-pitting: Coarse particles in mining dust contribute not only to optical shading but also to surface micro-abrasion, which subtly reduces light transmission even after cleaning.
The results show that soiling is especially severe in mechanized mining areas. This highlights the need for special strategies that provides the optimize solution for specific location.
Dust deposition plays a significant role in reducing the PV panel performance when deployed in mining environments. The study indicates a cyclic trend of performance degradation which is governed by local weather and mining activity. During the pre-summer phase (weeks 9–17), rapid performance decline was observed due to higher dust deposition (4.0–5.5 g/m²) and intense mining operations. In this period, maximum reduction of 63.54% in P_max of the dusty panel is recorded. This shows the critical impact of dust accumulation even under moderate solar radiation conditions. As shown in Fig. 7, week number 9 to 14 presents the higher rate of dust deposition and this period panel performance decreases significantly higher than other study weeks. During this phase, approximately 60–65% reduction in panel power suggest that the panel reaches a quasi-saturation level of dust deposition where further accumulation causes marginal additional losses. Therefore, to maintain power generation above 70% efficiency, a cleaning interval of 3 to 4 days is recommended for this mining site. This implies the requirement adopting a dynamic cleaning schedule which is a site-specific constant. During this week frequent cleaning of 3 to 4 days needs to be facilitated for efficient utilisation of solar energy. However, week 21 to 26 shows a comparatively low power reduction and this week is experiencing a declining rate in reduction of maximum power. A minimum reduction of 29.50% (in week 24) in P_max and maximum average solar radiation of 1020 W/m² (in week 21) is recorded during this phase of study. This offers a favourable operating condition for solar PV panel during this phase. Thus, cleaning frequency of 6 to 7 days is recommended for optimum utilisation of solar panels in mining environment. Here, even though week 21 offers a maximum average solar radiation but it perceived a highest reduction of 36.90% in maximum output power. This mainly results from the excessive dust deposition density during this period, which increases surface optical losses and thermal loading on the PV panel, thereby reducing photon absorption and electrical conversion efficiency despite higher irradiance. Moreover, intermittent factors such as partial natural cleaning, humidity variations, mild rainfall, and partial shading may have influenced the dust redistribution pattern rather than complete removal, leading to non-uniform soiling and localized heating, further contributing to performance degradation. Week 1 to 8 shows the increase trend of dust deposition and power reduction which indicates a moderate cleaning cycle of 6 to 7 days during initial phase (week 1 to 4) and fast cleaning with cycle of 3 to 4 days is recommended for optimum utilisation of solar PV panel.
A well maintained PV panel offers the average end of life of 20 to 25 years. Therefore, its maintenance structural stability can be maintained by providing less load (in terms of cleaning and external droppings) on its surface. The frequent cleaning operations subject the panel surface and mounting frame under cyclic mechanical stress which may harm the optical transmittance of surface glass. This approach maintains the structural reliability of the panel that help in maintaining its performance and end of life (EoL). Thus, optimizing cleaning frequency not only enhances annual energy yield but also extends the operational lifespan of PV systems in harsh mining environments.
The developed dust cleaning system was validated under actual mining field conditions to assess its operational performance and effectiveness in restoring solar panel efficiency. A crystalline PV panel of 10 W installed near the weighing bridge area of the active mining site. This is the same location where the comparative experiments between clean and dusty panels were performed. The purpose of choosing this site is to ensure the consistent environmental exposure and comparability of validated results. Three different representative validation phases such as Phase I (Winter–Early Dry), Phase II (Pre-Summer), and Phase III (Pre-Monsoon Transition) were selected from the 26-week study period. Each phase corresponds to a distinct dust deposition regime and irradiance condition. This analysis provides the validation of developed dust cleaning system under dynamic operating environments typical of mining zones. Figure 10 represents the performance comparison of the developed cleaning system across three validation phases. This shows the variation in the improvements of power generation of dusty panel, and its phase wise comparison is presented in Table 5. Table 5 indicates the comparison of P_max for dusty and cleaned panels during the three validation phases. The improvement percentage was calculated as the ratio of the increase in power output after cleaning to the corresponding dusty condition.
Performance improvement of dusty panel across three validation phases.
During Phase I, the highest improvement of approximately 45% was achieved after cleaning of dusty panel. This outcome corresponds to a moderate dust deposition density combined with lower relative humidity. This provides a dry contact of deposited dust over the panel surface, which is smoothly clean the panel surface when compared to other two phases. Thereby this phase showed more improvements in the panel performance. In contrast, Phase II exhibited the lowest improvement of nearly 30%. This is primarily due to dense, cohesive, clay-rich particulates that adhered more strongly under higher dust deposition density. Additionally, this phases experience the higher temperatures and humidity that bind the deposited dust more strongly than other two phases. This is why in this phase comparatively less improvements in the performance of dusty panel is observed. These fine, compact dust layers increased surface roughness and reduced light transmittance, resulting in limited irradiance absorption and lower current generation, even after cleaning.
Meanwhile, Phase III, demonstrated a recovery of about 42%, attributed to partial natural cleaning effects caused by mild rainfall, higher ambient humidity, and weaker dust adhesion. During this phase, deposited dust freely removed from the panel surface that help in restoring panel performance more effectively. The consistent range of recovery percentages (30–45%) across all three validation phases underscores the robustness and adaptability of the developed cleaning mechanism under dynamic mining environments. These results also confirm that panel degradation and recovery trends are strongly governed by dust load variability and environmental dynamics. By validating the dust cleaning system the potential for long-term deployment solar PV in harsh can be achieved. This not only improve the panel performance but also provides an effective cleaning mechanism that maintain the structural integrity of solar PV panel surface.
The findings of our study is well supported by the recent published work that shows the improvement of automated dry-cleaning systems for PV panel. A study conducted by⁴⁸ in 2019, used a silicone rubber brush for dry cleaning⁴⁸. This study reported a weekly improvements of about 16% compared to control panel whereas our study shows the average of 40% improvements in the panel eprofrmance. Our prototype uses a rolling brush and smart motor control, this help the cleaning system in maintaining this higher improvements. Further, in⁴⁹, a water-free cleaning robot was tested in China in 2022 which reports a maximum of 12% of improvements in the regular performance distributed PV settings. In cases of severe soiling, it improved performance by up to 25%⁴⁹. Our system did much better than these benchmarks in tough mining conditions. It showed great cleaning power and practical automation, perfect for dry environments. Field validation shows that our low-cost, waterless robotic cleaner beats old dry-cleaning methods. It also provides scalable, autonomous maintenance for large PV deployments.
Solar PV panels perform differently in outdoor settings. Dust can build up on them, but many environmental factors also play a big role. Relative humidity has two effects. It can cause dust to stick to the PV surface. This makes it harder to clean, especially in the early morning or during fog when moisture is high. This can make the panel’s surface stickier. As a result, the dry cleaning systems used in this study may work less effectively.
Wind speed is another crucial factor. Moderate to high wind speeds can have both positive and negative effects. Strong wind gusts can dislodge loose dust particles. This may slightly improve panel performance. High wind speeds in mining areas can lift many airborne particles. This speeds up dust settling and makes cleaning more necessary. This is especially important in open-pit mines. There, surface disturbances and blasting create even more dust.
Ambient temperature also affects PV efficiency through its interaction with panel voltage output. As temperature goes up, panel efficiency usually goes down. This happens because solar cells have higher internal resistance. In our study, ambient temperatures varied from 25 °C to 37 °C. This, along with dust loading, worsened the drop in overall performance. In hot, dry mining areas, these effects are stronger. This may require combining cleaning and passive cooling solutions.
Dust buildup is key to this study. Its severity changes based on particle size, mineral makeup, and electrostatic traits. For example, fine particles from iron ore mining tend to be highly adhesive and compact under solar radiation. These properties increase both the thermal insulation and shading effect on PV modules. This highlights how important it is to study dust at each site. Doing so helps us model performance losses accurately.
Our findings offer solid proof from one environment. However, we recognize that we cannot fully control or isolate the impact of each environmental factor. Future research should use studies across different sites and seasons. It should also include real-time weather data and dust chemistry from the surface. These efforts can help create predictive models. These models can change cleaning schedules based on local conditions.
Understanding these interactions is crucial for using solar PV in industry. This is especially true in dusty and hot places, like mines. A smart cleaning plan looks at dust buildup, weather, panel position, and how dust sticks. This approach makes solar energy systems more reliable and affordable.
The study shows that automated cleaning works well for small solar PV systems in dusty mining areas. However, we must recognize some limits before applying it on a larger scale. First, the cleaning system was validated on 10 W and 20 W panels in a single iron mine located in southern India. Dust particle size, makeup, and buildup rates here differ from those in coal, bauxite, or limestone mines. Airborne particles act differently depending on certain geological and operational conditions.
The system’s design may require significant customization. This is true for the sponge wiper and motor capacity, especially with larger panels or different array setups. The best cleaning schedule found in this study may not fit all situations. Places with more dust or finer particles might need cleaning more often. On the other hand, areas with regular rain or natural dust movement may require less cleaning. So, future plans should look into real-time dust monitoring. Also, dynamic cleaning schedules based on specific thresholds are important to consider.
Economic constraints also pose a challenge. Large-scale deployment can lead to higher costs for setup and upkeep. It may also cause syncing problems between arrays and increase the risk of mechanical wear over time. These challenges necessitate cost–benefit evaluations tailored to specific mining environments. Harsh conditions, like abrasive dust and extreme temperatures, can shorten component lifespans. So, the system may need more ruggedization.
In summary, the current findings are promising. However, to scale this solution, we need adaptive designs and strategies that fit specific contexts. Future research should test the system at different mining sites. It needs to cover various geological settings and dust levels. This will help ensure the system’s reliability and cost-effectiveness in different conditions.
This study reported a significant operational and economical loss of solar panel performance due to dust accumulation. A weekly power loss of approximately 35–45% was observed due to uncleaned solar panel in mining environment. This reduction is significant when compared to power loss in residential area. To extract maximum output power PV panel needs to clean regularly but over and under cleaning can disturb the effectiveness of solar PV installation. Over cleaning of solar panel may reduce the optical properties of glass and increase the cost of the operation. Thus, there is a need to maintain a proper balance among each cleaning cycle. This study recommend a weekly cleaning for the solar panel which is installed in the iron ore surface mines which is a day operative mines having mining operations such as exaction, hauling, drilling, blasting. The developed automated, waterless cleaning system demonstrated a gain of 38.46% in the output power of cleaned panel. This confirms the practical effectiveness of the developed cleaning system in maintaining energy efficiency under harsh, dust-intensive conditions. Such improvements translate to substantial gains in energy productivity, reduced manual intervention, and enhanced sustainability in industrial-scale PV installations.
Future work will focus on integrating a predictive maintenance framework that enable intelligent scheduling that monitor real-time dust accumulate data, weather conditions, and performance feedback. A comprehensive life-cycle cost analysis (LCCA) will also be undertaken to evaluate the economic feasibility and long-term return on investment (ROI) of deploying the system across diverse industrial sites. Further, the scalability and performance will be assessed for a larger PV installations under varying climatic zones, including arid, humid, and high-altitude mining regions.
Additionally, advanced statistical analyses such as confidence interval estimation, RMSE-based trend validation, and dust-type sensitivity analysis can be performed to develop an universal cleaning model. In addition to this, a comparative assessment across different mining environments such as arid zones in Rajasthan, humid mines in Odisha, and high-altitude operations in North East part of India will be performed. These efforts would help in establishing a flexible, data-driven and smart maintenance strategy that can dynamically adapt to local environmental and operational variations. This approach will provide an effective pathway to sustainable solar energy utilization in the mining industry and other high-dust sectors.
The purpose of this study is to collectively establish a quantitative framework for sustaining PV efficiency under harsh environmental exposure. This study investigated the impact of dust on the performance of solar PV panel in an active mining environment and optimized the cleaning frequency for enhanced energy recovery. Further, the study presents an innovative dry dust automatic cleaning system which is validated in the real mining condition. A systematic 26 week field analysis revealed that dust deposition density over the panel surface varied from 2.1 to 5.9 g/m² which is depends on the seasonal and surrounding operating conditions. The highest reduction of 63.50% and 53.57% in maximum output power (Pmax) and short circuit current of solar PV panel is recorded during the pre-summer phase. This characterized by dry weather and higher generation of dust deposition density due to intense mining activities. The pre-summer phase of weeks 9 to 17 witnessed an increase amount of dust deposition ranging from 4.0 to 5.5 g/m² in comparison to pre-monsoon where due to mild rainfall and particle cleaning reducing dust deposition density (ranging from 4.35 g/m² to 2.20 g/m²). The optimization study revealed the dynamically adjusted cleaning frequency based on the seasonal and operational variations in the mining environment. During the weeks 9 to 17, PV panels experienced the highest dust deposition density rate of 5.98 g/m² (in week 14) that indicates a more frequent cleaning cycle. Therefore, a cleaning interval of 3 to 4 day is recommended during this period to sustain more than 70% power efficiency. In contrast, the transition and late dry phases (weeks 21–26) exhibited comparatively lower dust loads and a minimum power loss of 29.50%. Thus, a moderate cleaning cycle of 6 to 7 day is recommended for this phase for optimal energy yield. The early winter–dry period (weeks 1–8) showed moderate deposition trends, due to this the initial cleaning frequency of 6 to 7 day is shifted to 3 to 4 days during the later phase of this period. By optimizing the cleaning cycle a less mechanical load can be maintained on the panel surface which improves its structural integrity. Thus, establishing a season-dependent and activity-responsive cleaning strategy not only enhances annual power recovery but also preserves the mechanical integrity and end-of-life reliability of PV panels.
Moreover, this study validated the developed automated dry-cleaning system under actual mining conditions using a 10 W PV panel setup. This validation across three environmental phases reports the average recovery of 40% in maximum output power of solar PV panel. This is a significant improvement for longer utilisation of solar energy in mining industry. The developed cleaning mechanism is light weight and low-friction system that ensured effective dust removal without visible surface abrasion. This confirms its suitability for prolonged use in abrasive mining environments. The study suggested the future work should be focused on integrating real-time dust sensing and AI-based decision algorithms to trigger adaptive cleaning events. Conducting long-duration durability tests to quantify mechanical wear and optical degradation of automated cleaning system may offer the sustainable utilisation of solar pV panel in harsh mining condition. The scaling of the developed cleaning system to clean multi-panel surface coupled with IoT-enabled cyber-physical system offer a robust predictive maintenance.
The datasets generated during and/or analysed during the current study are available from the corresponding author on reasonable request.
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Department of Mining Engineering, Aditya University, Surampalem, Andhra Pradesh, India
Abhishek Kumar Tripathi
Department of Mining Engineering, National Institute of Technology Karnataka, Surathkal, India
Mangalpady Aruna
Department of Mechatronics Engineering, Rajalakshmi Engineering College, Mevalurkuppam, India
E. Prakash
Department of Mechanical Engineering, Wollo University, Dessie, Ethiopia
S. Prabhakar
Faculty of Psychology, Shinawatra University, Bangkok, Thailand
Zhang Zhen
Department of Mechanical Engineering, Aditya University, Surampalem, India
P. V. Elumalai
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Tripathi, A.K., Aruna, M., Prakash, E. et al. Enhancing solar PV efficiency in mining operations through optimized cleaning intervals and automated dust mitigation. Sci Rep 16, 8718 (2026). https://doi.org/10.1038/s41598-026-42709-3
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SolarPower Europe strengthens Its long-term collaboration With Rystad Energy Through A New Prime Market Research Partnership  SolarQuarter
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“We’ve identified several hundred victims of the scheme. We think there might be more out there.”
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New York City has filed what it is calling a “landmark lawsuit” against William James Bushell, the owner of Radiant Solar. 
The Department of Consumer and Worker Protection alleged that the company’s clients were steered into expensive solar deals that failed to deliver on promised savings.
According to CBS News, DCWP Commissioner Samuel Levine said the alleged fraud was brought to the department’s attention from a CBS News New York investigation from last year. 
“When I came into this job, one of the commitments I made to the mayor and the people of the city is that we were going to take companies to court if they were ripping off New Yorkers,” Levine said. “That’s exactly what we’re doing with Radiant Solar.” 
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“We’ve identified several hundred victims of the scheme,” he continued. “We think there might be more out there.” 
While investing in solar is one of the best ways to save on energy costs, this story is a vital reminder to work with trusted partners when making major home investment decisions. 
Luckily, the experts at EnergySage can help, thanks to the company’s network of vetted solar installers. To get quick solar installation estimates and compare quotes, check out these free EnergySage resources.
While Levine intends to recover money for victims, Bushell’s attorney, Andrew Lustigman, has challenged the claims.
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“While our clients take the allegations seriously, they dispute the allegations, many of which are from years ago,” Lustigman said in a statement.
“While our clients remain committed to vigorously defending against the allegations, they are equally committed to continuing to cooperate with DCWP to address any concerns,” he continued.
For homeowners who worked with Radiant Solar, reported overpromises and installation issues led to significant problems with their systems and homes. 
One Radiant Solar customer, Erold Williams, said in a 2024 report that the company drilled into his roof even after he asked workers not to. Williams later said his ceiling collapsed as a result, leaving him responsible for repair costs.
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“It started by a drip, and the sheetrock start coming down,” the Bronx homeowner told CBS News.
Other homeowners say they were promised a zero-dollar electric bill, which never materialized.
“I’m hoping for some relief,” Lorna Wynter, another Radiant Solar customer, said. “I’m hoping [for] some answers.” 
Like any industry, solar has its share of bad actors and potential pitfalls that homeowners should be aware of before investing.
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VINCI Energies Guinea, a division of Moroccan company Cegelec, has officially launched the development of a 50 MWp solar power plant in Kindia, marking a significant step in the expansion of renewable energy infrastructure in Guinea. The project follows a €192 million contract signed with the Government of Guinea in April 2026 and is being implemented through Cegelec.
The initiative forms part of a broader two and a half year programme aimed at strengthening the country’s national electricity system and increasing the share of renewable energy in the generation mix. It is also designed to improve energy access and reduce reliance on thermal power, particularly in inland regions where supply constraints remain significant.
The project comprises a photovoltaic solar farm with a capacity of 50 MWp, covering approximately 80 hectares. In addition to generation assets, the scope of works includes the construction of around 350 km of overhead 225 kV transmission lines as well as two very high voltage transformer stations. These infrastructure components are intended to ensure efficient evacuation of power and integration into Guinea’s national grid.
Electricity produced by the plant will be fed directly into the national grid, supporting efforts to enhance energy sovereignty and improve grid stability. The infrastructure investment is expected to contribute to more reliable electricity supply while supporting broader economic development objectives.
Construction and commissioning will be carried out progressively over the duration of the project. More than 600 workers are expected to be deployed during the execution phase, with a strong emphasis on training local personnel and transferring technical expertise to Guinean teams.
Author: Bryan Groenendaal






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The Indian manufacturer is investing around $420 million to expand its manufacturing footprint alongside efforts to advance high-efficiency PV technologies through its partnership with ISC Konstanz.
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From pv magazine India
Indian PV manufacturer Solex Energy has signed a memorandum of understanding with the government of Gujarat to build a 5 GW solar cell manufacturing facility and a 10 GW battery energy storage system (BESS) factory in the state, with a planned investment of INR 4,000 crore ($420 million).
The company plans to develop the 5 GW factory in two phases: 2 GW in Phase I and 3 GW in Phase II.
Headquartered in Surat, Gujarat, Solex Energy currently operates a fully automated, Industry 4.0-enabled manufacturing facility in Tadkeshwar, Gujarat, with a PV module production capacity of 4 GW.
The company has recently expanded its technology roadmap through a partnership with Germany’s ISC Konstanz, focused on advancing high-efficiency solar cell technologies. The collaboration includes work on upgrading TOPCon cell lines and developing next-generation back-contact and tandem technologies.
In October 2025, the partners unveiled a rear-contact solar module concept based on n-type technology, offering up to 24.6% efficiency and 665 W output, with commercial production targeted for fiscal year 2027.
Under its Vision 2030 strategy, Solex Energy aims to scale its manufacturing capacity to 10 GW of modules and 10 GW of solar cells, aligning its expansion plans with ongoing investments in advanced PV technologies.
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CEEC, a China-based central enterprise, has started construction of a 900 MW integrated energy project in Xizang, with PV generation forming its largest component. The project includes 800 MW of PV capacity and 100 MW of solar thermal capacity in Wumatang Township, Lhasa, at 4.541 km altitude. Construction of the asset began on April 29, 2026, and the PV section uses a complementary model between agriculture and PV. This model is intended to combine PV power generation with ecological animal husbandry at the project site. The facility also includes solar thermal generation and 6-hour molten salt thermal storage for night-time generation, peak shaving, and basic power support. After completion, annual green electricity output will reach 1.56 TWh, equivalent to reducing 1.2512 million tons of CO2 emissions.

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Cloudy skies early. Scattered thunderstorms developing later at night. Low 72F. Winds SSW at 10 to 15 mph. Chance of rain 50%.
Updated: May 5, 2026 @ 11:52 pm
Protestors stand outside Bay Minette City Hall to oppose a proposed solar farm in Stockton on Wednesday, April 8, 2026.
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Protestors stand outside Bay Minette City Hall to oppose a proposed solar farm in Stockton on Wednesday, April 8, 2026.
The Baldwin County Commission voted Tuesday to ask the Alabama Attorney General’s Office to weigh in on whether it can hit the pause button on a 2,500-acre solar farm in Stockton. 
During its first meeting of the month in Bay Minette, Baldwin County commissioners voted unanimously to approve the step, which had previously been floated during a meeting in April. 
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The Baldwin County Commission will ask the Alabama Attorney General’s Office to decide if it can issue a moratorium on solar development while…
Despite a majority of people expressing concerns and opposition to a proposed solar farm in Stockton Wednesday night at a community meeting, t…
Stockton residents will have the opportunity to vote on whether to bring the area under zoning regulations, the Baldwin County Commission vote…
Less than two weeks after it was pointed out that an engineering firm may have had ties to a proposed solar project in Stockton, the Baldwin C…
An advocacy group opposing the development of a solar farm on 4,500 acres in Stockton is now raising concerns about an engineering firm county…
An anti-zoning effort that surfaced in Baldwin County amid resistance to a large solar field planned near Stockton for Meta data centers is be…
As several bills are moving through both the Alabama House and Senate to curb a solar farm development in Stockton, opponents are mounting a c…
Two solar farms proposed for 4,500 acres in Stockton off Highway 65 drew the ire of more than 200 Baldwin County residents and area advocates …
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Solar PV Panel Market Growth Driven by Renewable Energy Demand and Government Incentives  openPR.com
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The Netherlands Authority for Consumers and Markets is progressing with plans to introduce a grid fee that would see large-scale electricity producers, including solar power plants, contribute to the costs of the electricity grid. Its introduction is expected no earlier than January 2032. 
Image: Mladen Borisov/Unsplash
The Netherlands Authority for Consumers and Markets (ACM) is planning to introduce a grid fee for large electricity producers.
The tariff, expected to enter into effect from January 2032 at the earliest, will require large electricity producers, including solar power plants, to contribute to the costs of the electricity grid.
ACM says the tariff will “contribute to a more efficient utilization of the grid”, while adding that it would be entered gradually in order to give producers time to prepare for the change. 
A form of grid fee already exists in some European countries, including Belgium and Denmark, while Germany is working on similar measures. ACM says it plans to tie the level of the fee to the planned German tariff, as Germany is the largest trading partner of the Dutch energy market.
Several trade associations in the Netherlands have opposed the plan. Among them are trade association Holland Solar, which has said ACM’s decision on the tariff is leaving the market “in uncertainty.”
“The persistent uncertainty regarding the tariff level is causing delayed investment decisions, thereby slowing down the energy transition. This leads to higher costs for customers because more energy has to be imported from abroad,” a statement from the association adds.
Holland Solar is calling for ACM to provide clarity regarding the next steps as soon as possible and to work on structural solutions that “make the energy system more efficient without hindering the rollout of sustainable energy.”
“The energy transition requires clear and consistent policy. Delaying decisions does not help the sector move forward,” the association also said.
Last September, the Dutch government proposed amendments to its Environmental Decree to fast-track permitting for electricity transmission and distribution projects above 21 kV in a bid to expand grid capacity and ease congestion through 2032.
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STAFFORD COUNTY, Va. – A fire involving solar panels broke out on the roof of a Stafford County home Monday afternoon, but firefighters were able to quickly contain it.
What we know:
Fire crews were dispatched just before 2 p.m. to Beech Tree Court near Courthouse Road for a reported structure fire.
When crews arrived, they found smoke and flames coming from solar panels on the roof of a two-story, single-family home.
Firefighters worked to extinguish the flames and search the residence. Officials said the fire was contained to the solar panels and did not spread into the home.
No injuries were reported.
Officials credited the quick response for preventing the fire from extending further into the house.
What’s next:
The Stafford County Fire Marshal’s Office is investigating the cause of the fire.
The Source: This article was written using information from Stafford County Fire and Rescue.
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TYLER, Texas (KLTV) – Two East Texas counties are considering a partnership to study the effects of large-scale projects including solar farms and high-capacity water wells at no cost to taxpayers.
David Dunagan leads a group called Save Van Zandt County. He made the drive to Tyler on Tuesday to voice support for a possible partnership involving Smith and Van Zandt counties for what’s called a 391 commission.
“We woke up one morning and we found out that there were going to be 450,000 solar panels around us,” Dunagan said. “We don’t want that for any other citizen in any of these East Texas counties.”
The effort is backed by state lawmakers including Sen. Bob Hall and State Rep. Daniel Alders.
“Texas is growing by leaps and bounds, and that’s good in many ways, but not all growth is necessarily beneficial,” Alders said.
The commission is a planning tool allowed by local government code to study projects affecting health, safety and welfare.
The commission would study proposals to pump millions of gallons of groundwater out of East Texas along with large-scale solar farms and battery energy storage systems, specifically the fire hazards they bring and the loss of land.
“We don’t have the strengths that Collin County, Bexar County, Tarrant County has,” Smith County Commissioner Christina Drewry said. “And so, it’s important for us to partner with our neighbors so we can unite our voices and protect our citizens better.”
Smith County Judge Neal Franklin said the commission is not against development.
“We’re all about that here, economic development and bringing companies in,” Franklin said. “But we want them to do things on our terms.”
By law, state agencies like the Texas Commission on Environmental Quality and the Public Utility Commission would be required to work with the commission to “the greatest extent possible.”
“It doesn’t ask them to listen. It forces them to listen to our concerns,” Dunagan said. “And instead of rubber-stamping things, which they clearly do today on a lot of projects, it says ‘no, you will do this study and there is this information here and you will pay attention to it.’”
With developers often tight on time and not willing to wait, the commission could dissuade some of them.
“I won’t say necessarily a deterrent, but it makes them stop and think ‘is this the right place for us to try to build something?’” Dunagan said.
Smith County commissioners will vote next week on whether to join the commission. Other counties in the East Texas Council of Governments could also sign on.
Copyright 2026 KLTV. All rights reserved.

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Updated: May 5, 2026 @ 11:27 pm

GIBSON CITY — A California developer has withdrawn its application for a special-use permit for the construction and operation of a 2.25-megawatt solar farm on farmland just northeast of Gibson City.
Thirteen days after the city’s planning commission voted 6-1 to recommend the city council deny San Francisco-based ForeFront Power’s application, the company notified city officials of its request to withdraw.
The so-called “Ford Solar” project received pushback from several neighboring landowners during an April 21 hearing preceding the planning commission’s vote. The commission’s recommended denial of the application was expected to be considered by the council this month.
The project — owned by IL Solar Ford Project1 LLC, a company with the same listed address as ForeFront Power — was proposed to be built on a 23.42-acre triangular parcel of agriculturally zoned land at Ford County Road 600 East and Illinois 54 in Drummer Township.
No longer, though.
“Please accept this letter as the official withdrawal request from IL Solar Ford Project1 LLC of the Ford Solar (special-use permit) application for approval by the City of Gibson, Illinois,” stated the letter signed by Kristin Frooshani, vice president of ForeFront Power, and addressed to the planning commission’s chairman, Chase McCall, and deputy city clerk and advisor Jan Hall.
“We request you please withdraw our request from any action by the Gibson City Council for the special-use permit application. We also request you send us verification that the request has been withdrawn and will not be presented to the Gibson City Council for any action.”
McCall said neighbors voiced a number of concerns about the project, including its proximity to homes and the potential for the solar panels to cause glare issues and groundwater contamination.
Among the seven commissioners present, McCall was the only one to vote in favor of the issuance of a permit for the project. McCall said he did so because of the project’s potential benefits to the community, including the temporary stimulation of the economy through the creation of jobs, an increase in tax revenue from the involved land for local taxing bodies, and the possibility that the city’s residents could apply to receive energy credits on their utility bills via an agreement with Ameren Illinois.
“From a planning commissioner’s perspective, I have to think about what’s in the best interest for Gibson City,” McCall said.
The city has zoning authority within 1.5 miles of its corporate limits.

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Financial Trend: From Negative to Outstanding
Emmvee Photovoltaic Power Ltd delivered an exceptional financial performance in the quarter ending March 2026, prompting a significant upgrade in its financial trend rating from negative to outstanding. The company’s financial score surged to 32 from -16 over the past three months, driven by record-breaking operational metrics. Net sales reached a high of ₹1,738.81 crores, while profit before depreciation, interest, and taxes (PBDIT) soared to ₹571.11 crores. Profit before tax less other income (PBT less OI) stood at ₹478.91 crores, and net profit after tax (PAT) hit ₹392.38 crores. Earnings per share (EPS) also peaked at ₹5.67 for the quarter.
Operating profit to interest coverage ratio was an impressive 43.83 times, underscoring the company’s robust ability to service debt obligations. These figures highlight Emmvee’s strong operational efficiency and profitability, which have been pivotal in improving its financial outlook.
Quality Grade: Elevated from Average to Excellent
The company’s quality grade was upgraded from average to excellent, reflecting its superior fundamentals relative to peers in the electric equipment sector. Key quality metrics include an average EBIT to interest ratio of 4.34 and a manageable debt to EBITDA ratio of 1.53, indicating prudent leverage management. Emmvee’s return on capital employed (ROCE) averaged a strong 30.05%, signalling efficient capital utilisation.
Institutional holding stands at 14.74%, with zero pledged shares, which further supports the company’s governance and financial discipline. Compared to industry peers such as Waaree Renewable and Vikram Solar, which maintain average quality grades, Emmvee’s elevated quality rating positions it favourably for long-term growth prospects.
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Valuation: Downgraded from Very Expensive to Expensive
Despite strong fundamentals, Emmvee’s valuation grade was downgraded from very expensive to expensive, reflecting a moderation in market sentiment. The company currently trades at a price-to-earnings (PE) ratio of 16.72, which, while lower than some sector peers, remains elevated relative to historical averages. The price-to-book (P/B) value stands at 4.90, indicating a premium valuation for its net assets.
Enterprise value to EBITDA (EV/EBITDA) ratio is 10.42, suggesting that the stock is priced richly compared to its earnings before interest, taxes, depreciation, and amortisation. The return on equity (ROE) for the latest period is a robust 29.27%, supporting the premium valuation, but investors should be cautious given the stretched multiples. The PEG ratio is reported as zero, which may indicate a lack of meaningful earnings growth projections factored into the price.
Technical Indicators: Shift from Mildly Bullish to Sideways
Technical analysis reveals a shift in trend from mildly bullish to sideways, signalling uncertainty in near-term price movements. Weekly and monthly moving average convergence divergence (MACD) indicators are inconclusive, while the relative strength index (RSI) on a weekly basis is bearish. Bollinger Bands suggest mild bullishness on a weekly timeframe but lack confirmation on monthly charts.
Other technical tools such as the Dow Theory indicate a bullish weekly trend, but the on-balance volume (OBV) shows no clear trend, reflecting subdued trading momentum. The stock’s price has declined by 2.34% on the day, closing at ₹261.00, down from the previous close of ₹267.25. The 52-week high and low stand at ₹299.45 and ₹171.50 respectively, highlighting a wide trading range.
Comparative Returns and Market Context
Emmvee’s stock has delivered strong returns over recent periods, outperforming the Sensex benchmark significantly. Year-to-date (YTD) returns stand at 35.73%, compared to a negative 9.63% for the Sensex. Over the past month, the stock gained 20.11%, well ahead of the Sensex’s 5.04% rise. However, in the past week, the stock declined by 4.13%, while the Sensex inched up by 0.17%, reflecting some short-term volatility.
Longer-term returns are not available (NA) for one, three, five, and ten-year periods, but the Sensex’s 10-year return of 204.87% provides a benchmark for investors assessing Emmvee’s growth trajectory.
Want to dive deeper on Emmvee Photovoltaic Power Ltd? There’s a real-time research report diving right into the fundamentals, valuations, peer comparison, financials, technicals and much more!
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Institutional Participation and Risk Factors
One notable concern is the declining participation of institutional investors, who have reduced their stake by 1.8% over the previous quarter. Currently, institutional holdings stand at 14.74%, a relatively modest figure for a company with Emmvee’s market capitalisation and growth profile. Institutional investors typically possess superior analytical resources, and their reduced involvement may signal caution regarding the stock’s near-term prospects.
Additionally, while the company is net-debt free and boasts strong profitability, its valuation remains expensive. The price-to-book ratio of 4.90 and a PE ratio of 16.72 suggest limited margin for valuation expansion. Investors should also consider the stock’s recent short-term price weakness and sideways technical trend as potential headwinds.
Long-Term Fundamentals and Outlook
Emmvee Photovoltaic Power Ltd’s long-term fundamentals remain robust. The company has demonstrated strong growth in net sales, with a remarkable 234.8% increase reported in the latest quarter. Operating profit margins have also expanded, supported by efficient cost management and favourable market conditions in the photovoltaic sector.
Return on equity (ROE) is a healthy 29.3%, and the company maintains a net-debt-free balance sheet, which provides financial flexibility for future expansion. These factors underpin the company’s Buy rating despite the downgrade from Strong Buy, signalling confidence in its medium to long-term growth potential.
Conclusion
In summary, Emmvee Photovoltaic Power Ltd’s investment rating downgrade from Strong Buy to Buy reflects a balanced assessment of its current standing. Outstanding financial performance and excellent quality metrics are offset by expensive valuation and a sideways technical trend. The decline in institutional investor participation adds a note of caution. Investors should weigh these factors carefully, considering the company’s strong fundamentals against valuation risks and market sentiment.
With a current market price of ₹261.00 and a 52-week trading range between ₹171.50 and ₹299.45, Emmvee remains a compelling stock for investors seeking exposure to the photovoltaic power sector, albeit with moderated expectations.
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Is the global energy network ready for a solar charging market worth $2.88 billion by 2031?  openPR.com
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AI is draining Earth’s grid, Meta wants to plug into space  Cybernews
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Bluefield said it will advance a pipeline of utility-scale floating solar PV across the UK.
May 5, 2026
Having commissioned analysis that showed 40GW floating solar could be delivered in the UK by 2050, Bluefield Solar has launched a new business unit focused on the technology.
The utility-scale solar owner-operator launched the floating solar PV (FPV) business through its development arm and said it will now advance a pipeline of utility-scale FPV projects across the UK.
Bluefield commissioned analysis from independent consultancy CBI Economics that found that FPV is a “major growth area” for UK renewables. 
The company already owns and operates an FPV installation at the Queen Elizabeth II Reservoir, which the largest floating solar plant in the UK, at 6.3MW, and said it sees FPV as a strategic complement to ground-mounted solar, offering rapid deployment and the ability to be co-located with industrial and water-treatment demand. 
The largest approved solar plant in the UK is a 40MW project by port operator Associated British Ports, which received planning permission shortly before Scottish tidal energy firm Nova Innovation announced it will install 400kW FPV on an artificial lake in Cheshire.
Related:Elgin wins £500 million backing for 1GW UK solar and storage pipeline
Energy minister Michael Shanks commented on the report Bluefield commissioned, saying: “It’s time Britain stopped letting our solar potential float on by. 
“As this report shows, floating solar could generate the equivalent of around 11 gas power stations by 2040—cutting our dependence on volatile global gas markets we do not control.”
The report by CBI Economics found that, with the right policy environment, FPV could scale to 3.6GW by 2030, 18.3GW by 2040 and over 40GW by 2050. Bluefield noted that because reservoirs and similar managed water bodies are often located close to population centres, industrial clusters and AI growth zones, securing private-wire arrangements for high energy users to use energy generated by FPV plants can straightforward, sidestepping grid connection roadblocks.
Alongside the commercial and operational benefits for water companies and industrial users, CBI Economics also highlighted the environmental and system-level advantages that come with FPV.
These include improved drought resilience, because the floating arrays slow evaporation; reduced algal blooms; and, due to natural cooling from the water body, higher panel efficiency.
Aram Wood, appointed senior director of floating solar at Bluefield, said that to realise the potential of floating solar, “we need a policy framework that matches the urgency of the challenge,” but didn’t say what that framework might entail. 
Related:Octopus Energy enters Chinese energy market in JV with PCG Power
Floating solar projects are currently not eligible to bid for government support through the Contracts for Difference (CfD) scheme, which provides income certainty for renewable energy projects. 
One of the government’s Solar Roadmap actions is to address the viability of including FPV in the mechanism. 
Read more about:
Molly Green
Section Editor, Informa
Molly joined the team in 2024 and has led coverage on the UK sites. Now shifting to a more global view, Molly is interested in how legislation shapes market dynamics, covering the intersection of policy design, investment patterns, and energy transition pathways. 
Copyright © 2026 All rights reserved. Informa Markets, a trading division of Informa PLC.

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THE police on Tuesday, dragged a 28-year-old trader, Aliyu Sa’ad before a Life Camp Chief Magistrates’ Court in Abuja, for allegedly receiving stolen property.
Sa’ad, a dealer in fairly used items, who reside at Gidan-Bila Abuja, is standing trial on charges bordering on receiving stolen property.
He, however, pleaded not guilty to the charge.
The prosecutor, Charity Nwachukwu, told the court that the defendant committed the offence on April 27.
She alleged that a complainant, one Mr Abeng David , a Chief Security Officer CSO at Bali Bilad Estate Abuja, reported the matter at the Life Camp Police Station.
She told the court that the complainant had caught one Kabiru Danjuma with stolen solar panels while on security duty, adding that Danjuma eventually confessed to have previously stolen some solar panels.
According to the prosecutor, Danjuma also confessed that he sold the stolen iems to the defendant who allegedly received them knowing same to be stolen property.
She alleged that each stolen panel is worth N80,000, adding that the solar panels the defendant dishonesty received from Danjuma is worth N400,000.
According to her, during investigation and interrogation, the defendant made a confessional statement to the police.
The prosecutor said that all efforts to recover the stolen panels proved abortive.
The offence contravenes the provisions of Section 317 of the Penal Code.
The Chief Magistrate Mr Musa Jobbo, granted  the defendant bail in the sum of N500,000 with one surety in like sum.
The court ordered that the surety must reside within the court’s jurisdiction,
He adjourned the case to June 25, for hearing. NAN
A. A
MAY. 5, 2026

THE Federal Capital Territory (FCT) High Court sitting in Kurudu, Abuja, has declined jurisdiction to entertain a suit filed against…
THE Independent Corrupt Practices and Other Related Offences Commission (ICPC) has recorded a landmark judicial victory as the Supreme Court…
A 29-year-old man, Samson Ijuo who allegedly conspired with another to abscond with a minor, was on Monday dragged before…
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During a trial run in April, 2026, one of the most recent new CSP projects in China, the 100MW tower CSP project at Tangshan Haitai’s 1 GW Qiquanhu PV Industrial Park, set an operation record.
It ran continuously and safely around the clock for 96 hours straight, with daily generation exceeding 1 million kWh, according to an update from solar field supplier Shouhang Hi-Tech.
“The 72-hour trial operation of the unit started at 0: 04 on April 7th and ended at 0: 23 on April 11th, and it has been running safely and stably for 96h continuously, successfully fulfilling the set goal of continuous operation at full load for over 4h,” Shouhang noted in its report.
The 100 MW CSP project, located at the Qiquanhu PV Industrial Park in Turpan City, Xinjiang had had its initial commissioning checks in September 2025, per CSTA.
The 100 MW tower CSP forms the dispatchable core of a 1GW hybrid solar complex, firming up the co-located PV at the renewable energy park, like virtually all new CSP in China.
“The synergy markedly raises overall generation efficiency, system stability and power-supply quality, curbs renewable-energy curtailment, and offers a new route to overcoming bottlenecks in the development of large-scale renewable-energy bases, advancing a clean, low-carbon, safe and efficient modern energy system,” added Shouhang.
Tangshan Haitai, a hi-tech firm on the Beijing stock exchange, supplies all the associated 900 MW of PV. Haitai Solar is recognized as a BloombergNEF Tier 1 module manufacturer.
China Petroleum Engineering & Construction (CPECC Northwest), a CSTA vice-chairman unit is the General Contractor.
The thermal energy storage (12 hours) was designed and built by Bluestar (Beijing) Chemical Machinery, a subsidiary of Sinochem Holdings. Bluestar has supplied 15 thermal storage systems to CSP projects over the last decade.

Shouhang HiTech, whose Urat Trough CSP project in Inner Mongolia also broke generation records, has supplied the solar collection side; the heliostats, receivers and automated collection. Recently, Shouhang supplied the solar collection for the China Three Gorges Renewables 100 MW tower CSP at Golmud in Qinghai Province.
 
 
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South Africa rapid expansion of solar PV capacity is creating new opportunities for industrial development, but industry stakeholders warn that policy missteps could undermine both energy security and local manufacturing growth.
The South African Photovoltaic Industry Association has urged government to adopt a cautious and phased approach to the introduction of tariffs on imported solar components, highlighting the need to balance localisation objectives with continued market growth.
Recent estimates show that South Africa added between 2.5 and 3 GW of solar PV capacity over the past two years. Growth has been largely driven by embedded generation in the commercial and industrial segment, alongside increasing activity in the utility scale private off take market. Rooftop solar installations also surged in response to severe load shedding in 2023 and 2024, reshaping the electricity landscape, although adoption has since moderated and is now gradually rising again.
Despite strong demand, local participation in the solar value chain remains constrained. High value components including PV modules, inverters, trackers and lithium batteries are still predominantly imported, limiting the country ability to capture more value from the energy transition.
According to Rethabile Melamu, South Africa has yet to fully convert its solar boom into meaningful industrial growth. She notes that without clear policy alignment and a consistent long term demand pipeline, opportunities to build a competitive manufacturing base could be lost.
SAPVIA has played a key role in shaping policy frameworks such as the South African Renewable Energy Masterplan, which aims to link renewable energy deployment with industrialisation and job creation. While such initiatives signal intent, the association stresses the importance of prioritising components that can be competitively produced locally and scaled for both domestic use and export.
The Renewable Energy Independent Power Producer Procurement Programme remains central to utility scale deployment, while the private market continues to expand rapidly. However, future growth will depend heavily on accelerated grid infrastructure development.
Industry players are calling for greater certainty around procurement pipelines and policy direction. Manufacturers require visibility over a 5 to 10 year horizon to justify capital intensive investments in production facilities.
South Africa has made progress in selected segments of the value chain, particularly in balance of system components such as mounting structures and cables, where barriers to entry are lower and existing industrial capabilities can be leveraged. However, scaling production of higher value components remains challenging due to global competition, high input costs and infrastructure constraints.
SAPVIA emphasises that localisation efforts must be pragmatic. Attempting to localise the full value chain in the short term is neither feasible nor cost effective. Instead, a targeted approach is needed to build competitive advantage in selected areas.
The association warns that proposed tariffs on imported components should be introduced gradually to avoid undermining energy deployment. A balanced approach could support local industry development while maintaining momentum in renewable energy rollout.
Growing demand across the Southern African Development Community region also presents an opportunity for South Africa to position itself as a regional manufacturing hub, with neighbouring countries scaling up renewable energy programmes.
SAPVIA is advocating for coordinated action across energy, industrial and trade policy, alongside stronger collaboration between the public and private sectors. Priority measures include improved policy alignment, targeted industrial incentives, investment in skills development and enhanced infrastructure to support manufacturing competitiveness.
The association maintains that with the right policy framework, solar PV can drive inclusive economic growth, support job creation and strengthen South Africa position in the regional energy market.
Author: Bryan Groenendaal






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The French energy regulator has released the specifications for the ninth period of the PPE2 ground-mounted solar auction, covering projects above 500 kW and setting a submission deadline of July 30, 2026.
Image: X-Elio
From pv magazine France
Commission de régulation de l’énergie (CRE), the French energy regulator, has published the specifications for the “AO PPE2 PV Sol” tender covering ground-mounted and agrivoltaic solar installations.
The auction targets projects larger than 500 kW, including those partially integrating self-consumption schemes, and sets a total volume of 925 MW. A tranche of 200 MW is reserved for projects below 5 MW located more than 500 meters from another eligible project.
Bids can be submitted from July 20, 2026, with a final deadline of July 30.
In the event of tied scores, the lowest-priced bid is ranked first. If price and score are identical, the smaller-capacity project is prioritized.
The specifications also include supply chain resilience requirements. Eligible installations must not have photovoltaic systems assembled in a dominant non-EU third country, and at least four of eight key components must not originate from such a country.
These components include photovoltaic-grade polysilicon, silicon ingots, wafers, solar cells, solar glass, modules, inverters, and trackers with their mounting structures. Inverters, cells, and modules must be among the components meeting the origin diversification requirement.
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Shares of Jusung Engineering, a little-known industrial equipment maker in South Korea, have soared roughly 80% since mid-April, following reports that it stands to benefit if China restricts exports of solar manufacturing equipment. The stock surge has made Hwang Chul-joo, the company’s founder, chairman and CEO, a billionaire.
With his 26% stake, Hwang, 66, is the largest shareholder of Jusung Engineering, which is listed on South Korea’s technology-rich Kosdaq stock exchange. His wife, Kim Jae-ran, and his son, Eun-seok, hold an additional combined stake of just over 4%. Forbes estimates the net worth of Hwang and his family at $1.1 billion based on Monday’s closing price of 126,600 won.
Based in the city of Gwangju in Gyeonggi province near Seoul, Jusung Engineering makes equipment for mass production of semiconductors, solar cells and advanced digital displays. Its equipment specializes in thin-film deposition, which is the process of coating thin-film (atomic level) layers of chemicals onto a surface, such as a silicon wafer or glass substrate. The thin layers of chemicals help create the electrical circuits within microchips and maximize the light absorption in solar panels (raw silicon reflects some sunlight).
In a report published on April 21, Korea Investment & Securities analyst Chae Min-sook noted that “Jusung Engineering could effectively become the only alternative” should the Chinese government restrict exports of an advanced solar technology known as heterojunction to the U.S. Chae’s observation followed a Reuters report indicating that Chinese officials were mulling export curbs on advanced solar manufacturing equipment, including heterojunction technology, which is essential for producing high-efficiency solar panels.
This would provide a welcome boost to Jusung Engineering’s revenue and net profit, which fell last year due to increased research and development investments. The company reported a 67% drop in net income to 107 billion won on revenue that fell 24% year-over-year to 311 billion won (about $210 million) in 2025. The company draws the bulk of its revenue from the semiconductor business, supplying atomic layer deposition equipment to companies such as memory giant SK Hynix. Jusung Engineering is the world’s fourth-largest maker of atomic layer deposition equipment by market share, after ASM International in the Netherlands, Japan’s Tokyo Electron and U.S.-based Lam Research, according to research firm Gartner.
Hwang founded Jusung Engineering in 1993 and listed it in 1999. Previously, he worked at Hyundai Electronics (the predecessor to SK Hynix) and ASM International. He earned a bachelor’s degree in electrical engineering from Inha University in Incheon, west of Seoul.
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Power banks are a dime a dozen, but this one caught my eye with a feature I haven’t seen before: a built-in solar panel to recharge it using the power of the sun.
The Solly actually ticks a lot of boxes. Its 20,000-mAh capacity is enough to recharge your iPhone 17 Pro Max four times, and it’s got two Type-C ports capable of 140-W output for really quick charging. As you’d expect with these specs, it can also power laptops.
The battery itself is a solid-state affair, which means it uses a solid electrolyte instead of a flammable liquid one – so it should be safer to use in the long run, and won’t burst into flames when it’s damaged or even drilled into. The company also says this is housed in a shock-proof, water-resistant exterior.
We’ve only just started to see these arrive in the market; one of the first options I came across appeared last August. Solly says you can expect the battery in this one to retain over 80% of its performance and charge capacity over at least 3,500 cycles, or roughly three years of regular usage.
The device itself can be fully charged in just 26 minutes when plugged into a wall outlet. It can also serve as a travel adapter, with US, UK, and EU plugs available. An optional accessory makes it compatible with other outlet types for the rest of the world.
In addition, it supports pass-through charging, so it can simply power your devices when plugged in without charging the internal battery and deliver maximum output to your demanding gear, like a workstation laptop or gaming handheld.
If you’re outside, the solar panel wrapped around the exterior can top it off at a rate of 800-mAh per hour. That means you’ll need more than a full day of sunlight to fully recharge it, but if you’re in the middle of nowhere, that’s a whole lot better than nothing.
While there are solar power banks out there, I haven’t found any other model that also handles travel adapter duties, or features a solid-state battery. Plus, the Solly includes a third USB-A port to fast charge other devices, and a protective layer to keep the solar panel from getting scratched.
This model measures 3.15 x 2.36 x 1.38 in (8 x 6 x 3.5 cm), which is fairly compact – and the wall outlet prongs fold into the body to make it easier to slide into a pocket or bag.
The Solly is currently being crowdfunded on Kickstarter, where it can be had for as little as US$79 – discounted from its $115 expected retail price. You can get it in three different colorways, and add on neat accessories like a short Type-C cable that can double as a lanyard, and a charging dock to top off five Sollys at once.
All crowdfunding campaigns carry an element of risk, and this appears to a new brand’s first product – so you’ll want to keep that in mind if you choose to back this campaign. However, if all goes to plan, orders are slated to ship worldwide in August 2026, and delivery costs will be calculated later in the year.
Find the Solly on Kickstarter.
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The long-term value of a solar power plant depends on its ability to consistently deliver expected energy output. Soiling is a predictable and manageable factor that directly affects both performance and revenue. Addressing it through regular and structured cleaning practices is essential for maintaining efficiency and protecting returns.
Yogesh Kudale, Co-Founder & CEO, TAYPRO
TAYPRO
The solar industry has traditionally measured success through installed capacity. Megawatts commissioned and expansion targets have been the primary indicators of growth.
However, as the sector matures, the focus is shifting towards actual performance. The key metric today is how efficiently a plant converts its installed capacity into consistent energy generation.
In practice, most plants operate below their designed potential due to a combination of losses, many of which are manageable.
Soiling as a Performance Loss Factor
Solar panels operate in open environments and are continuously exposed to dust, pollution, bird droppings, and airborne particles. Over time, these elements accumulate on the module surface and reduce the amount of sunlight reaching the photovoltaic cells.
This accumulation, referred to as soiling, is one of the most common environmental and maintenance-related loss factors in solar power plants.
Under typical operating conditions, soiling can reduce energy output by up to 30 percent, depending on the location and surrounding environment.
Waterless robotic cleaning systems are specifically designed to address this issue in a consistent and scalable manner across utility-scale installations.
Impact on Energy Generation and Revenue
A reduction in irradiance directly affects energy generation, which in turn impacts revenue.
Even moderate efficiency losses can have measurable financial implications, particularly in utility-scale and commercial installations. Lower generation leads to reduced cash flow, extended payback periods, and pressure on expected returns.
At scale, these losses are not marginal. They accumulate over time and affect overall project performance.
This is where structured cleaning approaches become critical in maintaining output stability across large solar portfolios.
Cleaning as a Performance Intervention
Solar panel cleaning is one of the most direct and effective ways to restore performance losses caused by soiling. By removing the layer of accumulated contaminants, cleaning improves light transmission and enables panels to operate closer to their designed efficiency.
Field implementations have shown that consistent cleaning can improve energy output in the range of 6 to 10 percent in dust-prone conditions.
Across multiple deployments, automated cleaning solutions have demonstrated measurable improvements in generation while reducing dependency on manual intervention.
Importance of a Structured Approach
In many cases, cleaning is carried out reactively after a visible drop in performance. This approach results in avoidable generation losses before intervention takes place.
Maintenance-related losses increase when routine cleaning and inspections are not performed consistently.
A planned cleaning schedule, aligned with site conditions, ensures that soiling is managed before it significantly impacts output.
Advanced AI-driven scheduling systems enable cleaning cycles to be optimised based on environmental conditions, improving both efficiency and resource utilisation.
Evolving O&M Priorities
As solar projects scale and tariffs decline, operational efficiency is becoming increasingly important. There is a clear shift from capacity expansion to performance optimisation.
Within this context, cleaning plays a critical role because it offers:
Waterless robotic cleaning and predictive maintenance capabilities are increasingly aligned with this shift towards data-driven O&M strategies.
Conclusion
The long-term value of a solar power plant depends on its ability to consistently deliver expected energy output.
Soiling is a predictable and manageable factor that directly affects both performance and revenue. Addressing it through regular and structured cleaning practices is essential for maintaining efficiency and protecting returns.
As demonstrated across multiple large-scale projects, systematic and technology-driven cleaning approaches can improve generation consistency while optimising operational costs.
Solar panel cleaning should therefore be treated as an integral part of performance management, rather than a secondary maintenance activity.
 
The views and opinions expressed in this article are the author’s own, and do not necessarily reflect those held by pv magazine.
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Solar Power World
By SPW | May 5, 2026
 
I spent a week in Barcelona this April, and I left the Catalonian capital with the understanding that cities can be living things. They cannot breathe or think; they have no arteries carrying oxygen-rich blood or mouths with which to speak or eat. Yet, even without a brain, a city can bear a long memory of itself and evolve while embracing its lineage.
It’s difficult to describe what characteristics support this claim. At any hour, on any day in Barcelona, there seems to be a reason for people to gather in the most unexpected places. Many of the people who live there are open about what they support, draping flags from their balconies, hanging fliers in store windows or painting the words of causes onto walls and train cars.
While walking streets older than our country, I saw solar panels peeking over the parapet walls of ornate buildings. Enclosed bus stops throughout the city had brightly illustrated posters of construction workers installing solar panels – and these were issued by the Barcelonian government. The shelves of bookshops carried titles from Spanish publishers focused on environmental and climate issues.
I lived this week as a tourist — sampling the conveniences of a place afforded to those who don’t live there. For that reason, I acknowledge that my version of Barcelona is a skewed version of Barcelona. But in my nearly 33 years on this planet, places I’ve visited and lived have quickly homogenized to the point that you can find the same few things on any block in any major city in the United States.
Barcelona is also grappling with the same kind of commercialization and rising cost of living — as is everywhere else in the world. The difference is Barcelona is clinging tightly to its identity — a culture with centuries-old roots — while still embracing modern technologies like renewables.
The Barcelonian government itself has spearheaded deploying solar PV on municipal infrastructure. In 2027 alone, the city reportedly plans to install 381 solar projects on municipal buildings.
This maintenance of character feels rare in a contemporary context.
I understand — a city isn’t a county, isn’t a state, isn’t a country. Detractors can choose to handwave forward progress on critical infrastructure like a modernized grid powered by renewable energy, because it hasn’t been done yet. But a precedent isn’t a precedent unless someone sets it. We’re reeling from the whiplash of oil costs from yet another war, when there are still millions of roofs with space for solar.
We’ve already built so much renewable infrastructure here in the United States. There’s still much more that needs to be built to reduce our reliance on finite fuel sources. This issue of Solar Power World is focused on topics of maintenance and how we can ensure our progress isn’t lost in the process.
Billy Ludt, managing editor
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First Solar upgraded at Freedom Broker as Section 232 seen driving upside (FSLR:NASDAQ)  Seeking Alpha
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Chinese PV technology manufacturer Trina Solar has launched an “Australia specific” variant of its Vertex S+ modules featuring a power output of 515 W and a maximum efficiency of 24.65%.
Image: Trina Solar
Trina Solar has unveiled a variant of its Vertex S+ (TSM-NEG10R.28Z) solar module series that it says is designed to deliver a higher output within standard rooftop constraints and is tailored specifically for Australia’s residential and commercial and industrial (C&I) market.
“The Australian-exclusive module has been designed to support systems up to 100 kW under Australia’s Small-scale Renewable Energy Scheme (SRES), where higher wattage and efficiency per module allows installers to optimise system size and maximise Small-scale Technology Certificate (STC) returns within physical roof constraints,” Trina said.
The Chinese manufacturer said the monofacial NEG10R.28Z module delivers up to 515 W output with a maximum conversion efficiency of 24.65% within a standard rooftop module footprint of 1842 mm x 1134 mm x 30 mm. Built on Trina’s latest n-type i-TOPCon ultra cell architecture, the module incorporates zero-busbar and zero-gap technologies that the company said enhance efficiency and minimise electrical losses.
“This higher power density allows installers to achieve target system capacity with fewer modules and support higher system capacity without increasing footprint,” Trina said. “This contributes to lower balance-of-system (BOS) requirements and improved levelised cost of electricity (LCOE).”
The module’s open-circuit voltage is 38.3 V and the short-circuit current 12.85 A with Trina declaring the lower-voltage design enables more flexible string sizing, allowing installers to optimise system layouts across a range of inverter configurations.
“This provides greater design flexibility in rooftop applications, particularly where system configuration is constrained by roof layout or electrical limits,” the company said.
Trina said the design also reflects Australian operating conditions, with a low temperature coefficient of -0.26%/°C to support performance in high heat, and a dual-glass structure to improve durability. The module is also engineered to withstand mechanical loads of up to 5,400 Pa (snow) and 4,000 Pa (wind).
The product is backed by a 25-year product warranty and 30-year power guarantee. End power output is guaranteed to be no less than 88.85% of the nominal output power, while degradation in the first year should not exceed 1%.
Edison Zhou, Trina’s head of operations in Australia and Asia Pacific, said the product reflects a shift in the Australian rooftop solar market towards system optimisation.
“We see 510-515 W range as the practical ‘sweet spot’ for Australian rooftop systems,” he said. “Installers are consistently looking for higher wattage, higher efficiency modules that fit standard module dimensions, particularly where system design is constrained by roof size and configuration.”
“This allows for greater system capacity within a given footprint, while maintaining flexibility in system design depending on inverter selection.”
The Vertex S+ 515W module is available for preorder and is expected to be available in Australia from early Q3 2026, subject to final certification and product listing requirements.
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Grand Design is recalling more than 1,200 model year 2025-2026 Lineage motorhomes. The epoxy adhesive securing the solar panels to the roof may fail, allowing the solar panel to detach. As many as 1,269 RVs may be affected by the recall, which was issued April 30.
The cause of the issue is inadequate adhesion due to incompatibility between the epoxy adhesive and the roof and panel.
A detached solar panel can become a road hazard for other vehicles, increasing the risk of a crash and injury. For a motorhome’s driver, there is little or no warning that there is a problem.
Dealers will install mechanical fasteners, free of charge. Owner notification letters are expected to be mailed June 24.
Owners may contact Grand Design customer service at 1-574-825-9679. Grand Design’s number for this recall is M910059. This recall supersedes NHTSA recall 26V042.
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Media networks reported on May 3 that some lawmakers proposed looking into unregistered or informal solar installers over safety and regulatory compliance concerns.

Cristina Eloisa Baclig

Philippine Daily Inquirer

View all posts by Cristina Eloisa Baclig →

Philippine Daily Inquirer
View all posts by Cristina Eloisa Baclig →
Solar panel installation composite image. PHOTO: PHILIPPINE DAILY INQUIRER
May 6, 2026
MANILA – Calls to investigate so-called “guerrilla” solar installers have renewed attention on how the Philippines manages access to energy, particularly as more households turn to alternative sources amid high electricity costs.
Media networks reported May 3 that some lawmakers proposed looking into unregistered or informal solar installers over safety and regulatory compliance concerns.
The proposal has drawn mixed reactions, with some stakeholders raising questions about whether tighter oversight could affect the pace of renewable energy adoption, particularly at the household level.
RELATED STORY: Solar panel installers urged to register with DOE
For University of the Philippines Diliman professor and Inquirer data scientist Dr. Rogelio Alicor Panao, the discussion points to a broader tension shaping the country’s energy landscape.
“Recent calls for Congress to investigate ‘guerrilla’ solar installers highlight the friction between monopoly control and energy democratization,” he said, noting how the framing of the issue can influence both policy direction and public perception.
He added that the language used to describe these installers may carry unintended implications.
“While framed as a safety concern, the ‘guerrilla’ label not only unfairly stigmatizes citizens seeking relief from some of Asia’s highest electricity rates, but also casts doubt on motive since monopolies stand to gain the most when decentralized competition is strictly curtailed,” he said.
Untapped potential and structural barriers
Data from the World Bank reinforces the idea that the country’s challenge is not a lack of solar resources. The Philippines posts a practical photovoltaic potential (PVOUT) of 3.93 kWh per kWp per day—placing it in the midrange globally but among the stronger performers in Southeast Asia.
As Panao pointed out, “Our solar potential is nearly 10% higher than Vietnam’s (3.55) and is neck-and-neck with Thailand (4.06).”
Yet this relative advantage has not translated into widespread adoption. Looking at broader development patterns, Panao noted that countries with strong solar potential often face structural constraints that limit their ability to capitalize on it.
“The data also reveals a negative correlation (-0.43) between solar potential and the Human Development Index (HDI), indicating that nations with the most to gain from solar often face the highest systemic barriers,” he said.
In the Philippines, where the HDI stands at around 0.70, these constraints take on added significance.
“For the Philippines, where the HDI is approximately 0.70, solar is not a luxury but a critical tool for development that remains capped by a regulatory environment seemingly designed to preserve the status quo,” he said.
Rather than viewing the issue solely through enforcement, Panao’s analysis points to policy gaps that shape both large-scale and small-scale adoption. If the goal is to expand access to solar energy, he said, reforms will need to address bottlenecks across the system.
“If Congress is truly serious about tapping the Philippines’ solar potential, it can explore the following as policy actions,” he said, outlining measures that range from streamlining approvals to supporting decentralized systems.
RELATED STORIES: DOE drafts registration rules for solar PV system vendors
Among these is the need to ease permitting for utility-scale projects by establishing administrative “one-stop shops” and enforcing strict processing timeframes to eliminate the red tape that continues to stall large-scale deployment.
At the same time, Panao underscored the importance of ensuring that smaller producers—now an increasingly visible part of the energy mix—are supported rather than constrained.
“Second, it should establish a balanced policy environment for distributed photovoltaic systems that protects small-scale producers rather than penalizing them,” he said.
In an archipelagic country like the Philippines, decentralized systems take on added importance, particularly in expanding access to areas beyond the reach of traditional grids.
“Third, the government must support the adoption of decentralized off-grid and mini-grid systems, which are the most cost-effective way to bring power to remote island communities and provide urban backup,” he said.
Sustaining that momentum, Panao said, will depend not only on expanding access but also on keeping solar technologies affordable and better integrated into the grid.
“Finally, by maintaining the cost-reduction trajectory for solar components and supporting the development of smarter inverter systems for better grid integration, the Philippines can transition solar energy from a marginalized, unregulated activity into a primary energy right for every citizen, ensuring that clean power is accessible to the public rather than restricted by dominant market interests,” he said.
RELATED STORY: EXPLAINER: How to keep your solar panels safe from fire
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China Energy Engineering Corporation has successfully connected the 30 MW Dekemhare Solar Plant to Eritrea’s national grid at full capacity in Dekemhare, marking a significant milestone in the country’s power sector development and its transition toward cleaner energy systems.
The facility is now the largest solar installation in Eritrea and the first centralised renewable energy plant in the country to be paired with a utility scale battery energy storage system rated at 15 MW with 30 MWh capacity. The integration of storage with solar generation is expected to significantly enhance grid stability by managing variability in solar output and ensuring more consistent electricity supply.
The project more than doubles Eritrea’s existing solar generation capacity and represents a strategic shift away from dependence on diesel powered generation, which has historically been both costly and environmentally intensive. By displacing diesel generation, the plant is expected to reduce fuel import requirements while improving overall energy security.
Located in Dekemhare, an area known for strong solar irradiation levels, the installation is positioned to maximise generation efficiency and support broader electrification objectives in the region. The combination of high resource availability and integrated storage provides a practical model for scaling renewable energy deployment in similar markets across Africa.
The addition of battery storage allows excess daytime solar energy to be stored and dispatched during peak demand periods, reducing intermittency challenges that often limit renewable energy penetration. This capability is particularly important for emerging power systems seeking to balance reliability with rapid expansion of renewable capacity.
The commissioning of the Dekemhare Solar Plant highlights the growing role of hybrid renewable energy and storage solutions in supporting energy access and grid modernisation efforts in Africa’s developing power markets.
Author: Bryan Groenendaal






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The Ministry of New and Renewable Energy (MNRE), in its seventh Approved List of Module Manufacturers (ALMM) for solar cells, has added Renewsys India Pvt. Ltd. and revised the solar cell manufacturing capacity for Waaree Energies, marking another update in India’s approved domestic manufacturing base.
MNRE has enlisted Renewsys India Pvt. Ltd. with a manufacturing capacity of 452 MW per year for its bifacial N-type TOPCon solar cells (182.2 mm × 183.75 mm, 16 busbar, PID-free). These cells report an average efficiency of 24.60%, with an efficiency range of 24.00% to 25.60%. The wattage is specified at 8.23 W, ranging from 8.03 W to 8.54 W. The enlistment is valid from April 30, 2026, to April 29, 2030.
Waaree Energies has revised the enlisted capacity for its manufacturing unit in Chikhli, Navsari, Gujarat. The facility continues to hold an enlisted capacity of 1,328 MW per year, with updated performance metrics. The revised efficiency range now stands at 22.00% to 23.70%, with wattage ranging around 7.85 W (min–max). Earlier figures indicated an efficiency range of approximately 22.00%–23.70%, with previously noted wattages between 7.36 W and 7.85 W.
Continuing with the same capacity under the ALMM listing, where Waaree had reported an output of 1,328 MW per year for monocrystalline PERC (P-type) bifacial solar cells (182.2 mm × 182.2 mm, 10-busbar, PID-free). Now the company has revised the average efficiency of the cell to 23.55% and a wattage of 7.78 W, with an efficiency range between 22.20% and 23.50%. Similarly, continuing with Waaree’s earlier enlistment of 3,923 MW/year for its WSC-N-M10R-16BB mono TOPCon solar cells, but it has now revised the range of efficiency to 24.0% -25.80% and 8.00 W to 8.68 W.  
India had earlier seen India pass the 30 GW solar cell manufacturing mark, driven by fresh additions and capacity upgrades reflected in the latest update to the Ministry of New and Renewable Energy’s (MNRE) Approved List.
Among the key additions, Reliance Industries Limited has been enlisted for its Jamnagar, Gujarat facility with a capacity of 1,238 MW per year for advanced heterojunction (HJT) solar cells (210 mm × 105 mm, no busbar, PID-free). These high-efficiency cells deliver an average efficiency of 25.40% with a wattage of 5.60 Wp per cell. The enlistment remains valid from April 13, 2026, to April 12, 2030.
Jupiter Solartech Private Limited secured its third enlistment under ALMM-II, adding around 991 MW per year of mono PERC bifacial solar cell capacity. This builds on earlier enlistments of Jupiter International Limited (Units 1 and 2), which had added 339 MW and 440 MW per year, respectively, in June 2025 at its Baddi facility in Himachal Pradesh. The company has now expanded further with Unit III in the same industrial cluster.
Meanwhile, Websol Energy System Limited has scaled up its enlisted capacity to 1,202 MW per year at its Falta Special Economic Zone facility in West Bengal. The upgraded capacity covers mono-crystalline PERC (P-type bifacial) cells in 182.2 mm × 182.2 mm and 182.2 mm × 183.75 mm formats (10 busbar, PID-free) under the WS182MP10 category. These cells achieve an average efficiency of 23.55% with a wattage of 7.77 W, and operate within a range of 19.00% to 23.60% efficiency and 6.29 W to 7.88 W.
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Solar Power World
By Kelly Pickerel | May 5, 2026
The Sun Pond solar and storage project in Maricopa County, Arizona, is now online. The 111-MW solar and 340-MWh storage project was developed by Longroad Energy and constructed by McCarthy Building Companies. 
Two California utilities, Ava Community Energy and San José Clean Energy (SJCE), have contracted for the output of Sun Pond via long-term PPAs.
“With Sun Pond now operational, Longroad is pleased to be expanding access to renewable energy for customers in the greater Bay Area,” said Charles Spiliotis, Chief Investment Officer and co-founder of Longroad Energy. “Sun Pond’s battery storage system adds firm, flexible capacity – ensuring low-cost, clean power is available when the grid needs it most.”
Sun Pond is part of the Longroad Sun Streams Complex, a four-project complex totaling nearly 1.6 GW of solar and storage capacity  in Maricopa County, Arizona. The entire Longroad Sun Streams Complex is providing more than $300 million in benefits to Arizona schools and communities through its long-term leases with the Arizona State Land Department and tax remittances.
Longroad employed the Gridstack battery energy storage system from U.S.-based energy storage platform provider Fluence for the Sun Pond BESS. Sun Pond utilizes First Solar’s PV modules, Nextpower’s smart trackers and Sungrow’s solar inverters.
McCarthy was the EPC contractor. More than 300 people were employed across all contractors and teams at peak construction. NovaSource Power Services and Longroad’s affiliate Longroad Energy Services will provide comprehensive operations and maintenance services.
News item from Longroad
Kelly Pickerel has more than 15 years of experience reporting on the U.S. solar industry and is currently editor in chief of Solar Power World. Email Kelly.

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EDP Weighs Sale of US Unit Focused on Small-Scale Solar Power  Bloomberg.com
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The Madison College chapter of the National Society of Leadership and Success recently inducted 14 new members during its spring induction ceremony…
Madison College recently marked a sustainability milestone with a ribbon-cutting ceremony for its new solar plus energy storage system at the Truax Campus Protective Services Building.
The solar project is designed to enhance reliability, reduce environmental impact and help lower operating costs.
Along with these benefits, the system also offers a hands-on learning laboratory for students and educators.
“At our campuses, students gain hands-on experience with innovative technologies that prepare them for clean energy careers,” said Dr. Jennifer Berne, Madison College president. “At the same time, we are advancing sustainable, reliable energy solutions for our region.”
The April 20 ribbon-cutting ceremony was part of a series of “Earth Week” events held at the college. Other activities included a sustainability tour, free bike tune-ups, a sustainability fair and trash pick-up throughout the campus.
Features of the new large-scale battery energy storage installation at the Protective Services Building include:
The project will offer an opportunity for students to study solar performance in programs such as Renewable Energy Certificate, Electrical Apprenticeship, Electrical Technical Diploma, Construction Technical Diploma, Industrial Maintenance AS, Electromechanical Technology AS and Architecture AS.
“This solar plus storage installation provides infrastructure for training students for skilled technical careers in the energy workforce,” said Madison College instructor Ken Walz.
The $665,000 solar plus energy storage project was supported in part by a $435,000 award from the Wisconsin Energy Innovation Grant Program.
“The project demonstrates Madison College’s commitment to protecting our planet, responsibly stewarding our operations and advancing our mission to serve students,” said Dr. Sylvia Ramirez, the college’s executive vice president of finance and administration.

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The Ann Arbor Sustainable Energy Utility will use locally sited solar, batteries and other resources to improve reliability and lower costs for subscribers, city officials say.
The homes participating in the pilot program are located in Ann Arbor’s Bryant neighborhood, where A2SEU held a March meeting seeking residents willing to become its first customers.
Bryant has more energy-burdened residents than Ann Arbor as a whole, with some locals spending upwards of one-third of their household income on utility bills, FranklinWH said. Neighborhood median income is well below the citywide average, according to local media outlet MLive.
At the meeting, Jordan Larson, engagement innovator with the city of Ann Arbor’s Office of Sustainability and Innovations, showed a chart illustrating how enrolled homes would self-consume some of the power generated by their panels and store the rest in batteries for discharge during the evening and overnight hours.
“All of the work in this project is focused on reducing total energy costs,” Larson said.
In 2024, nearly 80% of Ann Arbor voters approved a referendum to create a city-owned utility that would help accelerate the city’s clean energy goals and boost local resilience. The Bryant solar-plus-storage pilot is the first step toward a future that A2SEU says could feature microgrids, geothermal heating and cooling networks, and energy justice initiatives for the roughly 125,000 inhabitants of the university town 40 miles west of Detroit.
“Unlike a traditional utility, we are only going to offer renewable energy products, including solar and geothermal that will come later to this neighborhood and hopefully all around the city,” Shoshannah Lenski, A2SEU’s executive director, said at the March meeting.
A spokesperson for DTE Energy, the investor-owned utility that serves Ann Arbor, Detroit and surrounding communities, said it supports A2SEU’s sustainability goals in a statement comparing the municipal program to DTE’s own voluntary clean energy program.
“When coupled with DTE’s planned investments in clean energy, these voluntary, fee-based programs help accelerate economy-wide decarbonization while maintaining reliability and affordability,” Ryan Lowry, the spokesperson, said in an email.
A2SEU says energy storage will help its subscribers ride through power outages and — along with other onsite power generation — boost overall system reliability by “[minimizing] the need for distribution systems (e.g., poles and wires), which are currently the most vulnerable part of the existing energy system.”
A 2025 report from the Citizens Utility Board of Michigan, a utility watchdog group, found Michigan’s power grid experienced longer-duration outages over the past five years than all but a handful of other states. DTE is spending billions to upgrade its distribution grid and says its reliability has improved significantly since 2023.
Lowry said DTE’s “five-year, $270 million plan to modernize the electric system that serves the city” helped it deliver “the best electric reliability Ann Arbor has experienced in nearly 30 years” in 2025.
For the time being, A2SEU enrollment is optional for Ann Arbor residents and its generating resources supplement rather than replace DTE’s assets. But a citizen group calling itself Ann Arbor for Public Power is gathering signatures for a November ballot initiative that could start the years-long process of creating a full-fledged public utility in the city. DTE has spent nearly $2 million opposing the effort, according to financial disclosures reviewed by MLive.
Lowry said “municipalization” in Ann Arbor would cost residents and taxpayers $1 billion upfront and increase energy bills in the city by a “minimum” of 30% to 40%, per a DTE-commissioned report released in early 2025.
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The PJM Interconnection’s planned backstop auction is flawed, said CEO Brian Tierney. Separately, Pennsylvania Gov. Josh Shapiro said his administration will oppose rate hike requests that fail to meet affordability criteria.
The reliability watchdog is concerned about a series of “widespread and unexpected” customer-initiated load reductions in 2024 and 2025 during which 1,000 MW or more dropped off the bulk power system.
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The PJM Interconnection’s planned backstop auction is flawed, said CEO Brian Tierney. Separately, Pennsylvania Gov. Josh Shapiro said his administration will oppose rate hike requests that fail to meet affordability criteria.
The reliability watchdog is concerned about a series of “widespread and unexpected” customer-initiated load reductions in 2024 and 2025 during which 1,000 MW or more dropped off the bulk power system.
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Scientific Reports volume 16, Article number: 12293 (2026) Cite this article
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This study analyzes the power production (PP) and energy yield of four 100 kW PV subfields, consisting of monocrystalline and polycrystalline technologies, with fixed and single-axis tracking systems. All subfields are installed at a 30° inclination, close to the region’s optimal angle. Actual performance data were recorded every four minutes in OUED-NECHOU, Ghardaïa, over four experimental days in 2016, each representing a different season. The results indicate that single-axis tracking subfields consistently outperformed fixed systems throughout the diurnal cycle by generating more power and enhancing overall performance. However, on May 1^st, the fixed mc-Si and pc-Si subfields reached peak outputs of 95.67 kW and 84.06 kW, respectively, surpassing the motorized subfields, which recorded 88.35 kW and 83.01 kW. Conversely, on July 1^st, the single-axis tracking systems achieved their highest daily energy generation, with the mc-Si subfield producing 787.94 kWh/day and the pc-Si single-axis system generating 715.17 kWh/day. Further analysis of mean power output augmentation demonstrated that single-axis tracking subfields consistently outperformed their fixed counterparts, which served as the baseline across all experimental days, with the highest gains observed in east–west tracking systems. On July 1^st, the mc-Si tracking system achieved a 19.22% increase over the fixed mc-Si subfield, while the pc-Si tracking subfield exceeded its fixed counterpart by a remarkable gain of 21.44%. Moreover, tracking systems exhibited a clear advantage in maximizing solar energy capture, leading to higher energy production. Finally, the impact of weather conditions, including solar irradiance, temperature, wind speed, and relative humidity, on PV subfield power generation was experimentally analyzed.
Energy production presents a significant challenge for the near future. Currently, fossil fuels remain the primary source of global energy, contributing heavily to greenhouse gas emissions and accelerating climate change. The rapid depletion of these finite resources, due to excessive consumption, emphasizes the need for sustainable alternatives Haddad et al.¹ and Saiah and Stambouli². In this context, the demand for renewable energy sources has become increasingly urgent. Renewable energy, particularly solar, wind, and hydropower, is gaining recognition as a viable solution to meet the rising global energy demand. However, the intermittent nature of these sources necessitates efficient and cost-effective energy storage solutions. Zhang et al.³ presented a thorough review of iron-based redox flow batteries (Fe-RFBs), which are becoming a promising solution for large-scale energy storage. Their study examined the historical development, essential performance factors, and recent advancements in Fe-RFB technology. It emphasized the advantages of Fe-RFBs, including their cost-effectiveness, environmental benefits, and potential to facilitate the integration of renewable energy sources. The findings highlighted that iron-redox flow batteries (Fe-RFBs) have advantages such as a long cycle life and scalability, but they still face challenges. These challenges included mitigating hydrogen evolution, improving electrode stability, and enhancing overall efficiency. To tackle these issues, the authors recommended optimizing electrode materials, developing cost-effective active components, and refining system design to boost performance and commercial viability. These advancements have the potential to significantly improve energy storage capacity, thereby contributing to the stability and sustainability of renewable energy systems.
These advancements could significantly improve energy storage capacity, Promoting the stability and sustainability of renewable energy systems and given the increasing reliance on solar energy, integrating efficient energy storage benefits, particularly in sun-rich regions like Algeria.
With its exceptional year-round sunshine, Algeria is well-positioned for large-scale solar energy deployment⁴. In recent years, government initiatives have driven significant progress in renewable energy, including establishing of photovoltaic power plants in the Saharan regions to enhance solar capacity. For example, as part of its renewable energy strategy for the Saharan regions, Sonelgaz (The National Gas and Electricity Society) has established photovoltaic power plants in the OUED-NECHOU region of Ghardaïa. These plants, managed by SKTM (Electricity & Renewable Energy Company), have a combined production capacity of approximately 1.1 MW. Ensuring that these photovoltaic modules operate reliably for 20–25 years under field conditions is critical to maintaining profitability⁵. This initiative underscores Algeria’s commitment to clean energy and sustainable development, paving the way towards a greenr and more eco-friendly future Dahmoun et al.⁶. Understanding the performance of photovoltaic (PV) systems is essential for evaluating the potential of solar energy as a reliable power source. Analyzing the efficiency and operation of these systems provides valuable insights into their maintenance needs and long-term economic viability Dahmoun et al.⁶. PV systems rapidly emerged as a dominant sustainable electricity source, representing a promising alternative to conventional energy sources. Their performance, however, depends largely on the technology used and the system’s design. Numerous studies have assessed PV plant performance in various geographic regions, emphasizing how local environmental conditions influence system efficiency. Large-scale photovoltaic public–private partnership (LS-PVPP) projects have been analyzed globally, with findings from some reported in the literature Ascencio-Vasquez et al.⁷. Bentouba et al.⁸. For instance, Shiva Kumar and Sudhakar⁹, studied a 10 MWp photovoltaic plant in India, reporting a yield factor (YF) ranging from 1.96 to 5.07 h per day, an annual performance ratio (PR) of 86.12%, and a capacity factor (CF) of 17.68%, with an annual energy generation of 15,798.192 MWh. Similarly, Touili et al.¹⁰. They found that a 100 MWp plant in the MENA region produces an average of 158 GWh annually. In comparison, the same configuration generates 155.8 GWh annually in Almeria, Spain, and 155.4 GWh in Bakersfield, California. Maximizing the performance of photovoltaic (PV) solar panels relies on capturing as much sunlight as possible. Solar tracking systems are a key technology in achieving this, as they enable PV panels to continuously align with the sun’s movement. By adjusting along vertical or horizontal axes, these systems optimize electricity production by ensuring that the panels are always positioned to capture maximum sunlight. As noted by Gomez-Uceda et al.¹¹. Photovoltaic plants equipped with sun tracking systems are designed to follow the sun’s trajectory, ensuring that panels remain perpendicular to the solar rays throughout the day, thereby maximizing power generation. Numerous studies have analyzed the efficiency of solar tracking systems compared to fixed installations. George et al.¹². Two off-grid PV systems in Italy one fixed and the other equipped with a daily single-axis solar tracker were analyzed. Their results indicated higher power production in the morning and evening with the single-axis tracker, in contrast to the fixed system. This supports the broader consensus in the literature that tracking systems consistently outperform fixed PV systems in terms of energy generation Nsengiyumva et al.¹³, Chien-Hsing et al.¹⁴. Further studies by Zaghba et al.^15,16 demonstrated that solar tracking systems significantly increase energy capture compared to stationary systems. Vaziri Rad et al.¹⁷ examined various tracking systems across different regions of Iran, finding that twin-axis trackers increased energy generation by 32%, while single-axis trackers led to a 23% increase compared to stationary systems. These findings highlight the critical role of tracking technology in enhancing the efficiency and overall performance of photovoltaic power plants. Recent literature documents both significant advances and practical challenges in solar tracking technologies. The comprehensive review by Kumba et al.¹⁸ summarizes performance gains achievable with modern trackers while also highlighting the trade-offs of increased mechanical complexity, maintenance requirements, and the need for robust control algorithms. Empirical work on alternative mechanical architectures such as the second-order lever single-axis tracker evaluated by Kumba et al.¹⁹ demonstrates that innovative designs can improve solar capture and reduce actuator demands under real field conditions. Field studies in high-irradiance environments, such as the Manta, Ecuador case study Ponce-Jara et al.²⁰, further confirm that well-designed single-axis tracking systems can significantly increase daily and long-term energy yield, especially when tailored to local irradiance and operational constraints. In addition, recent work by Kumba et al.¹⁹ investigated second-order lever single-axis solar tracking systems, demonstrating improved energy output over conventional trackers. While partial shading was not specifically studied, the results highlight the potential of optimized mechanical architectures to enhance energy capture under dynamic solar angles. In harsh desert-type climates such as OUED-NECHOU—characterized by high irradiance, dust accumulation, and occasional shading—these design principles are particularly relevant. Building on these concepts, our experiments indicate that optimized single-axis tracking systems, incorporating features inspired by second-order lever architectures, can substantially increase long-term daily energy production. Local factors such as dust storms, ambient temperature fluctuations, and maintenance logistics must guide system selection and operation. Overall, our study confirms that advanced tracking technologies, when adapted to site-specific conditions, can improve energy yield and system resilience in Saharan regions. Recognizing that efficiency and performance are essential aspects of a PV system’s functionality, they have been the focus of an extensive body of literature. Numerous studies Pendem and Mikkili²¹, Kumar et al.²², Bahanni et al.²³, Kawajiri et al.²⁴ emphasize that various factors, including solar irradiance, ambient temperature, module temperature, wind speed, relative humidity, materials, and the mounting of PV modules. Caouthar Bahanni et al.²⁵ conducted a comparative analysis of the energy performance and the influence of meteorological conditions on three photovoltaic technologies (monocrystalline, polycrystalline, and amorphous) installed in two Moroccan cities, Beni Mellal and El Jadida. Using data from one year of operation (January to December 2017), the study assessed the production performance of identical PV stations in distinct climates. The results demonstrated that photovoltaic performance is strongly influenced by meteorological factors. Solar irradiation was identified as the dominant factor, with higher irradiation directly increasing output. Temperature also had a significant impact; rising temperatures led to a reduction in PV cell voltage and power output. Wind speed provided moderate benefits by cooling the panels, slightly improving efficiency, while humidity had the least impact, primarily affecting production through cloud cover. Notably, polycrystalline panels exhibited the highest performance in Beni Mellal, followed by monocrystalline, with amorphous panels being the least efficient. Temperature significantly influences the energy output, power output, and overall efficiency of photovoltaic systems. Amelia et al.²⁶ conducted research that conclusively demonstrates that as module temperatures increase, the output power and efficiency of PV panels decrease. Karami et al.²⁷ conducted a study on the performance of monocrystalline, polycrystalline, and amorphous solar modules installed on the rooftops of an educational institute in Morocco. The results showed that the maximum performance ratio (PR) achieved was 72.10%, 91.53%, and 86.20% for cloudy days due to low temperature and high wind speed. Conversely, the minimum PR values and PV module efficiency were observed on quiet sunny days and rainy days, impacting the energy generated. The significance of module temperatures in the performance of solar PV systems is highlighted in the articles by Malvoni et al.²⁸. Al-Maghalseh²⁹, and Kumar et al.³⁰. To accurately evaluate the performance of PV systems, various models, such as those proposed by Correa-Betanzo et al.³¹ have been suggested for estimating module temperatures. A comparative study by Olukan and Emziane³² examines 16 temperature models based on monthly mean meteorological data. The investigation analyzes how module temperatures fluctuate in response to changes in solar irradiation ranging from 100 to 1000 W/m² and varying ambient temperatures. The results indicate a temperature range for the modules from 31.8 to 66 °C across different months. The study emphasizes the performance differences among the models, underscoring the appropriateness of each model for the optimal sizing and design of PV systems. Additionally, Wind speed is a crucial parameter that significantly affects photovoltaic (PV) system performance. While its impact on power production can vary, wind plays a vital role in cooling solar panels, which enhances overall energy output by improving module efficiency. For instance, Balta et al.³³ observed that consistent wind on PV panel surfaces positively influenced both cooling and the cleaning of dust deposits in Amasya, Turkey. Similarly, Al-Bashir et al.³⁴ found that increased wind speed resulted in lower cell temperatures, subsequently boosting output power in PV systems installed in Jordan. Humidity, on the other hand, negatively impacts the performance of PV systems. Water droplets in the air and condensation on panel surfaces diminish the solar irradiation reaching the modules, thereby affecting their efficiency. Ramli et al.³⁵ conducted experiments under various weather conditions dusty, cloudy, and rainy in Surabaya, Indonesia, demonstrating performance loss associated with these factors. Furthermore, heightened air humidity often leads to persistent cloud cover, complicating solar energy production. Despite this, humidity remains a significant variable influencing the performance of photovoltaic systems. Building on these findings, numerous studies have explored critical comparisons between fixed and sun-tracking photovoltaic systems, assessing their efficiency, energy yield, and operational effectiveness. Research also includes performance evaluations of PV systems across different climates, large-scale experimental assessments, and the impact of temperature and irradiation on energy production. Furthermore, advanced approaches such as PV cooling techniques and energy-exergy analysis have been examined to enhance system efficiency. Moreover, experimental studies conducted at large-scale PV centers across different regions provide valuable insights into real-world system performance. To effectively highlight key findings, the following literature review table provides a structured summary of relevant studies, emphasizing their contributions to PV system performance analysis and identifying gaps for future research. This tabular presentation systematically outlines the research gaps and the contributions of this study, clearly illustrating the novelty of our work (Table 1).
This study aims to provide a comprehensive analysis and evaluation of the performance of four photovoltaic subfields, each employing different configurations: two single-axis tracking systems and two fixed systems, incorporating both monocrystalline (mc-Si) and polycrystalline (pc-Si) silicon technologies. Conducted in the Saharan environment of OUED-NECHOU, Ghardaïa, at the SKTM Electricity and Renewable Energy Company unit, this research examines performance under actual weather conditions rather than Standard Test Conditions (STC). The study focuses on key performance metrics, including peak output power (kW), long-term daily power production (kW), and the average daily output power (kW) over each of the four observed days, accounting for seasonal variations. It also evaluates the performance improvement of single-axis tracking systems compared to fixed photovoltaic subfields, with a focus on the gain in output power expressed as a percentage (%). To ensure precise data collection and analysis, daily energy generation (kWh/day) was measured at four-minute intervals. Additionally, this research examines the influence of real-time weather data, recorded at the same intervals, on subfield performance. Key factors include solar irradiation at a 30° tilt (W/m²), ambient temperature (°C), module temperature (°C), wind speed (m/s), and relative humidity (%). The analysis considers seasonal climatic variations and their influence on these meteorological parameters throughout specific experimental days in winter, spring, summer, and fall. A section of this study intends to predict the total solar radiation flux at a 30° tilt using semi-empirical models, specifically the PERRIN DE BRICHAMBAUT model. The expected results will be compared with experimental data recorded in real-time at four-minute intervals over four measured days: January 1^st, May 1^st, July 1^st, and October 1^st, each representing a different season. Data was collected from a weather station installed on the roof of the photovoltaic station’s control room. Statistical indicators used for comparison between the estimated and measured data include the Absolute Error curve (AE) , Mean Absolute Error (MAE, W/m²), Root Mean Square Error (RMSE,W/m²), Correlation Coefficient (CC), and Mean Absolute Percentage Error (MAPE, %). the objective is to determine if the empirical model aligns most closely with the real data based on these statistical tests.
The Ghardaïa photovoltaic solar power plant, located in southern Algeria, is part of the renewable energy development program initiated by the supervisory ministry. It is situated near the village of OUED-NECHOU, 15 km north of Ghardaïa along National Road No. 01 as in Fig. 1, with a nominal power capacity of approximately 1100 kWp. The site is bordered by National Road No. 01 to the north and west, and vacant land to the east and south. The plant’s precise coordinates are 32°34′43.79’’ N latitude and 3°41′55.36’’ E longitude, at an altitude ranging from 450 to 566 m. The closest wilayas are Laghouat and Ouargla. The topography of the site is relatively flat, with a gentle east–west slope.
Geographical location of the photovoltaic power plants: 1.1 MWp OUED-NECHOU, Ghardaïa City ⁴⁶.
Ghardaïa’s hot, dry climate presents extreme environmental conditions, with temperatures ranging from − 5 to + 50 °C in the shade. Wind speeds can reach up to 28 m/s, and the maximum recorded relative humidity is 74% at 25 °C. Solar irradiations during the summer months can reach 900–1000 W/m². The area also experiences significant temperature fluctuations between day and night 15 to 20°C and frequent winds carrying fine sand particles, factors critical for plant design and maintenance. Despite these challenges, the plant is located in seismic zone 0, indicating low seismic risk as per Algerian regulations (RPA 99).
Researchers and professionals in photovoltaic technology and power plant performance emphasize the importance of understanding regional environmental conditions. Constance Kalu et al.⁴⁷ utilize 22 years of meteorological data from NASA’s global database, including solar insolation and air temperature, to perform a comparative analysis of polycrystalline, monocrystalline, and thin-film PV technologies using PVsyst version 5.21. Similarly, Allouhi et al.⁴⁸ employed METEONORM 7 data, including wind velocity, ambient temperature, and solar irradiance, to compare the performance of monocrystalline and polycrystalline PV technologies. Their study evaluates a 2 kWp grid-connected PV plant in Meknes, Morocco, combining recorded data from 2015 and simulated results to assess the power generation capabilities of these technologies. Al-Otaibi et al.⁴⁹ assessed the performance of CIGS thin-film PV systems installed on rooftops in Kuwait by monitoring key meteorological parameters such as solar radiation, ambient temperature, wind speed, and module temperature. Using a reference cell and pyranometer for solar radiation measurements, the study recorded data at five-minute intervals over twelve months to evaluate the impact of environmental factors on PV system efficiency in Kuwait’s climate.
It is crucial to have accurate weather data to evaluate and optimize the performance of photovoltaic systems. This necessitates using advanced technical instruments to gather experimental data on local weather conditions.
The meteorological station’s data acquisition system is installed on the rooftop of the Technical Room at the photovoltaic power plant. It is equipped with devices that provide essential climatic information, including 30° tilted solar irradiance (W/m²), ambient temperature (°C), wind speed (m/s) and direction, and relative humidity (%). Data were collected every 4 min from 06:00 AM to 19:52 PM on January 1^st, May 1^st, July 1^st, and October 1^st, representing different seasons (Winter, Spring, Summer, and Fall). Table 2 shows a list and specifications of instruments used by manufacturers.
Figure 2 presents experimental relative humidity data measured with a thermo-hygrometer over four days, from 06:00 AM to 19:52 PM. Each curve corresponds to a different day. The data reveal a consistent diurnal pattern, with higher humidity levels in the early morning and night, decreasing during the day and late afternoon, indicating a regular daily cycle. On October 1^st, relative humidity peaked at 90% at 06:00 AM, gradually reducing to 42% by 19:52 PM. A similar trend was observed on January 1^st, where humidity started at 67% at 06:00 AM and dropped to 45% by 19:48 PM. On May 1^st and July 1^st, relative humidity was significantly higher in the early morning, with readings of 42% at 06:00 AM on May 1st and 35% at the same time on July 1^st. Throughout the day, humidity levels steadily decreased, reaching 17% by 19:52 PM on May 1st and dropping to 10% by 19:52 PM on July 1^st (Figs. 3, 4).
Relative humidity data (%) over four experimental days , each representing a different season in 2016 .
Wind speed data (%) recorded over four experimental days, each representing a different season in 2016.
PERRIN DE BRICHAMBAUT estimated inclined solar radiation compared with experimental data on January 1^st 2016, a winter day.
The variation in humidity levels is due to the significant diurnal temperature fluctuations in the OUED-NECHOU region Figs. 5, 6, and 7. Intense heating during the day can lead to very low relative humidity, while in the early morning and at night, temperatures drop sharply, causing a brief rise in relative humidity. The RH data inversely correlates with the daily temperature cycle: as temperature increases, RH decreases, and vice versa.
PERRIN DE BRICHAMBAUT estimated inclined solar radiation compared with experimental data on May 1^st 2016, a spring day.
PERRIN DE BRICHAMBAUT estimated inclined solar radiation compared with experimental data on July 1^st 2016, a summer day.
PERRIN DE BRICHAMBAUT estimated inclined solar radiation compared with experimental data on October 1^st 2016, a fall day.
Figure 3 showcases experimental wind speed data from 06:00 AM to 19:52 PM over four days, each curve represents data from a different season, measured using an anemometer.
On January 1^st, the wind speed starts at a low of 0.02 m/s at 6:00 AM and reaches a peak of 2.56 m/s in the late afternoon at 6:32 PM. On May 1st , the wind speed peaks at 8.37 m/s in the early morning around 6:04 AM and again at 9:16 AM, then drops to 4.16 m/s by late afternoon around 7:48 PM. On July 1^st, the wind speed shows a rapid increase from 7.22 m/s in the early morning at 6:00 AM to 9.05 m/s by 7:24 AM, then decreases rapidly to reach 1.03 m/s, the lowest value recorded on that day, at 6:08 PM. On October 1^st, the wind speed peaks at 7.20 m/s around noon and drops to 2.67 m/s by late afternoon at 7:48 PM.
Wind speed changes are influenced by temperature variations. In summer, intense heat from the Sahara desert causes air to rise, creating low pressure and stronger winds, as observed on July 1^st. In winter, the smaller temperature difference between the desert and surrounding areas leads to weaker pressure gradients and lower wind speeds, as seen on January 1^st.
Figures 2 and 3 illustrate an inverse relationship between relative humidity (%) and wind speed (m/s) in the OUED-NECHOU region. High wind speeds with low humidity are observed in spring and summer (May 1^st and July 1^st), while low wind speeds with high humidity occur in winter and fall (January 1^st and October 1^st). This indicates that as wind speed increases, relative humidity decreases, and vice versa.
Photovoltaics offer a clean and promising energy solution, making the study of solar resources crucial for this field. A 2017 case study by Bill Marion and Benjamin Smith⁵⁰ developed a method for estimating solar radiation using PV module data with microinverters, validated with data from five systems in Golden, Colorado. The study accurately extracted direct normal irradiance (DNI) and diffuse horizontal irradiance (DHI), which are essential for developing and modeling PV projects in the region.
Various semi-empirical models documented in the literature have been extensively employed to investigate solar radiation on both horizontal and inclined surfaces.
A study conducted in Ouargla, which has similar climatic conditions to our study area, OUED-NECHOU in Ghardaïa, was carried out by Abdelmoumen Gougui et al.⁵¹. The study compared three models (CAPDEROU, PERRIN DE BRICHAMBAUT, and Hottel) for predicting total solar flux on horizontal surfaces using data from a weather station at the LAGE laboratory, Ouargla University. The data was recorded on the 15th of March, April, May, and October. The models were evaluated using RMSE, CC, and MAPE metrics in MATLAB. The results showed that the PERRIN DE BRICHAMBAUT and CAPDEROU models exhibit greater effectiveness under clear skies in Ouargla, demonstrating a high degree of accuracy and correlation between observed and predicted global solar radiation, this model outperforms the Hottel model. Additional studies on horizontal solar radiation across various regions offer further insights and findings^52,53,54,55.
Abdelatif Takilalte et al.⁵⁶ developed a methodology to estimate global tilted irradiation at 5-min intervals using only global horizontal irradiation data. This approach integrates the PERRIN DE BRICHAMBAUT and LUI & JORDEN models, adjusted for cloudiness factors, to create an anisotropic model. The proposed model demonstrated high accuracy across various metrics, including nRMSE (4.7–6.41%), RPE (5.5–5.9%), nMAE (3.07–4.73%), and R² (0.97 to 0.99), especially for short time steps. Compared to conventional and ANN models, the proposed model showed smaller errors, confirming its superior performance. Simultaneously, Moummi et al.⁵⁷ conducted a comparative study using data from the Biskra meteorological station to evaluate the PERRIN DE BRICHAMBAUT and LIU & JORDEN models for calculating daily global radiation on an inclined plane. The study found that both models effectively simulated solar irradiance, with the LIU & JORDEN model aligning better with experimental values at sunrise and sunset and the PERRIN DE BRICHAMBAUT model being more accurate around solar noon. This study serves as a reference for our research due to the similar solar radiation patterns in Biskra and OUED-NECHOU and the use of comparable methodologies. Additionally, other studies^58,59,60 have focused on predicting global solar radiation for inclined surfaces, providing results from various regions.
The following excerpt details an experimental comparison study at the 1.1 MWp photovoltaic power plant in OUED-NECHOU, Ghardaïa. A weather station installed on the rooftop of the technical room at the centre of the plant was used to gather authentic data on solar radiation at a 30° tilt. The overall radiation reaching the Earth’s surface at this angle includes direct, diffuse, and reflected irradiances as depicted in (1).
G_T = Global inclined solar radiation [W/m²].
S = Direct radiation on an inclined plan [W/m²].
D_ciel = Diffuse radiation on an inclined plan [W/m²].
D_sol = Ground reflection radiation on an inclined plan (albedo) [W/m²].
Experimental real-time data was collected using a pyranometer every 4 min, from 06:00 AM to 08:00 PM, over four days in 2016. To estimate the theoretical global irradiance in the OUED-NECHOU region, the PERRIN DE BRICHAMBAUT semi-empirical model was employed, incorporating the linke atmospheric turbidity factor along with atmospheric and astronomical parameters. The equation for global solar irradiance at a 30° tilt was derived using previously obtained geographical data of the region.
Using MATLAB software, the PERRIN DE BRICHAMBAUT model with the Linke atmospheric turbidity factor was applied to simulate the total theoretical inclined irradiance. The results were plotted in Figs. 2, 3, 4, and 5 and compared with experimentally inclined irradiances collected over four days representing each season: January 1^st (Winter), May 1^st (Spring), July 1^st (Summer), and October 1^st (Fall) of 2016.
The graph displays a comparison of inclined irradiances over four days, featuring the experimental data (red curve) and theoretical data (blue curve). It also highlights the absolute error (yallow curve) between these datasets and presents ambient temperature measurements (green curve).
The solar irradiance results show a strong correlation between measured and predicted data on January 1^st (a winter day) and October 1^st (a fall day), particularly at sunrise, sunset, and midday. On January 1^st, the experimental peak solar irradiance was 927.61 W/m², with a predicted value of 865.45 W/m² around midday. On October 1^st, the maximum measured value was 1021.9 W/m², while the estimated value was 980.94 W/m².
On May 1^st (a Spring day), there was a fluctuation in the experimental solar irradiance data compared to the estimated data from 6:00 AM to 12:00 PM. This fluctuation was due to a sharp increase in wind speeds, as shown in Fig. 3, where the highest value recorded by the anemometer sensor reached 8.37 m/s, resulting in instability in the inclined solar radiation during that time. However, from 12:00 PM to 6:00 PM, there was consistency between the experimental and estimated data. The highest value for experimental solar radiation was 1121.6 W/m², while the estimated solar radiation was 1057.3 W/m², both recorded around midday.
On July 1^st (a summer day), we observed consistency between the measured and estimated data from 6:00 AM to 10:00 AM. However, from 10:00 AM to 6:00 PM, disturbances began to appear in the real solar radiation data. These disturbances were due to the changing wind speeds and the presence of clouds, which prevented the passage of solar radiation. The wind speed data on this day was the highest among the four experimental days, with the anemometer sensor recording a maximum of 9.05 m/s. Furthermore, the maximum measured value of solar irradiance was 891.28 W/m², while the estimated value was 1036.2 W/m².
In their study of solar radiance in Biskra, Moummi et al.⁵⁷ concluded that variations in solar radiation data throughout the day are primarily due to climatic disturbances. Similarly, Benbouza Naima et al.⁶¹ demonstrated through images in her study of solar radiation in Batna, Algeria, that several natural factors, including wind and clouds, can significantly affect solar radiative flux, leading to instability in the collected data.
The performance of the semi-empirical model was validated using statistical parameters⁵⁴, including MAE, CC, RMSE, MAPE, and the absolute error curve. These indicators are commonly used in the comparison and assessment of solar radiation models, as highlighted in the literature^{52,53,54,55,56,57,58,59,60,61,62,63,64,65,66}. The results of the statistical analysis over four experimental days are shown in Table 3.
The statistical indicators (MAE, RMSE, CC, and MAPE), evaluated over four days in 2016, demonstrate that the PERRIN DE BRICHAMBAUT semi-empirical model closely matches the actual data.
July 1^st (a summer day) provides the best accuracy for the solar radiance predictions based on the MAE values, with an MAE of 52.2668 W/m². This reflects the smallest average error in the predictions compared to the other days analyzed, indicating superior predictive accuracy. Furthermore, on July 1^st, the model achieved its highest accuracy with the lowest RMSE of 4.2737 W/m², reflecting close alignment between predicted and actual solar radiance values and demonstrating strong performance. The more, the correlation coefficient (CC) of the model is consistently high, exceeding 0.7 over the four measured days, with the highest value of 0.9668 observed on July 1^st. This high CC value indicates a strong correlation between observed and estimated solar radiance in tilt of 30°.These results suggest that the model performs well in correlating observed and estimated values across all days, demonstrating robust predictive capability. The MAPE, which quantifies accuracy as a percentage, shows excellent results with values below 10% for all days. The best performance was observed on July 1^st, with a MAPE of 1.9684%, highlighting the model’s robustness and reliability in estimating inclined solar irradiance.
We can confidently conclude that the PERRIN DE BRICHAMBAUT model provides a good fit and correlation between measured and predicted global solar radiation over four observed days. The model is particularly effective for regions with latitudes below 60°, in line with findings from the Atlas Solaire de l’Algérie⁶⁴. Therefore, this semi-empirical model can be used to predict global inclined solar radiation at a 30° tilt in photovoltaic power plants in OUED-NECHOU, Ghardaïa, even in the absence of a pyranometer instrument.
The power plant, constructed by S.P.E. (Algerian Electricity Production Company), is located approximately 15 km north of Ghardaïa, near the village of OUED-NECHOU. The site spans ten hectares and houses a photovoltaic plant designed to harvest and directly convert sunlight into electricity.
With a nominal power of approximately 1100 kWp, the plant aims to evaluate the performance of various photovoltaic technologies in the southern Algerian environment, where conditions such as high solar radiation and temperature extremes can significantly impact efficiency. This pilot project is divided into eight sub-fields, each containing four photovoltaic modules of different technologies and two types of structures (fixed and motorized). The installation is oriented towards the south (azimuth angle = 0°) and inclined at an angle of 30°.
The Table below represents the central constitution of the photovoltaic power plants at OUED-NECHOU, Ghardaïa distributed as follows:
Figure 8 provides an overview of the PV accessory center at OUED-NECHOU, showcasing the primary photovoltaic technologies present at the site.
Monocrystalline silicon panels (452 kWp).
Polycrystalline silicon panels (452 kWp).
Amorphous silicon (a-Si) panels (100 kWp).
Thin film panels (cadmium telluride CdTe) (100 kWp).
Illustrative Image of the OUED-NECHOU photovoltaic power plant in Ghardaïa, showing its PV subfields inclined at 30° Facing South.
These images were obtained during an experimental study conducted at the center.
This study presents an experimental comparison of four photovoltaic subfields configured as two fixed and two single-axis tracking systems, all inclined at 30°. Each subfield consists of a series-connected array of photovoltaic modules, with each subfield having a capacity of approximately 100 kW. The objective is to evaluate the performance of these photovoltaic technologies, specifically monocrystalline silicon (mc-Si) and polycrystalline silicon (pc-Si), which share identical material compositions but differ in structural configuration. The experiment was conducted over four days under identical meteorological conditions at the OUED-NECHOU site, with specific climatic conditions representative of southern Algeria. Detailed technical parameters are provided below.
Sub-field (1) has a capacity of 105 kWp and features a motorized monocrystalline silicon (mc-Si) structure. The peak power output of each photovoltaic (PV) panel is 250 Wp. This sub-field comprises 420 photovoltaic modules, organized into 21 chains, with each chain consisting of 20 modules.
Sub-field (2): has a capacity of 98.7 kWp with a Motorized polycrystalline silicon structure (pc-Si), and the peak power output of the PV panel is 235 Wp. This sub-field comprises 420 photovoltaic modules, organized into 21 chains, with each chain consisting of 20 modules.
Sub-field (3) has a capacity of 108 kWp with a fixed thin- film structure using Cadmium Telluride (CdTe), and the peak power output of the PV panels 80 Wp .This sub-field comprises 1260 photovoltaic modules, organized into 105 chains, with each chain consisting of 12 modules.
Sub-field (4): has a capacity of 100,116 kWp with a fixed amorphous silicon structure (a-Si), and the peak power output of the PV panel is 103 Wp .This sub-field comprises 972 photovoltaic modules, organized into 54 chains, with each chain consisting of 18 modules.
Sub-field (5) has a capacity of 105 kWp with a Fixed monocrystalline silicon structure (mc-Si), and the peak power output of the PV panel is 250Wp.This sub-field comprises 420 photovoltaic modules, organized into 21 chains, with each chain consisting of 20 modules.
Sub-field (6): has a capacity of 98.7 kWp with a Fixed polycrystalline silicon structure (pc-Si), and the peak power output of the PV panel is 235 Wp. This sub-field comprises 420 photovoltaic modules, organized into 21 chains, with each chain consisting of 20 modules.
Being an experimental site, the Ghardaïa photovoltaic plant was chosen to use four different types of panels and two types of support structures: fixed structures or mobile (motorized tracking systems).
The subfields containing either fixed structures or automated tracking systems are discripted above Either the fixed structures or the motorized structures will be installed on the ground through concrete blocks. The structures will be made of galvanized steel, and sized in accordance with site conditions. The fixed structures will be oriented towards the south with a tilt angle of 30°, to optimize the sunshine on the panels see Fig. 9.
Fixed structure of the photovoltaic system in the OUED-NECHO subfields for monocrystalline (mc-Si) and polycrystalline (pc-Si) technologies.
The tracking systems will be of the single-axis type, with the axis oriented in the east–west direction. Throughout the day, the tracker follows the sun’s movement from sunrise to sunset, using (azimuthal tracking) from east to west . The panels installed on the tracker will be tilted at a 30° angle to enhance sunlight capture. This configuration maximizes the angle of incidence of sunlight on the panels throughout the day, thereby improving the efficiency and power output of the photovoltaic system compared to fixed-tilt systems. Additional details about the motorized structures are shown in Fig. 10.
Single-axis tracking structure of the photovoltaic system in the OUED-NECHO subfields for monocrystalline (mc-Si) and polycrystalline (pc-Si) technologies.
Each tracker is moved by an electric motor located on the system and powered by a low voltage (LV) panel of the power plant Fig. 11.
Motorized tracking system for the PV subfields (SLAVE).
The movement of the tracking systems is synchronized by a proprietary control system (PLC). Tracking systems will need to return the modules to horizontal for high wind speed.
The functional operation of the single-axis tracking system, as illustrated in Figs. 10 and 11, is described as follows:
During operation, the tracking mechanism followed a stepped movement protocol: each drive chain was activated for approximately 5 s, followed by a 10-min rest period, in sequential order across 21 chains. This gradual motion minimized actuator wear and reduced energy consumption. Position control relied on mechanical limit switches and predefined end stops, as the system lacked high-resolution encoders due to its legacy design. This stepped strategy provided near-continuous sun-following while significantly reducing motor duty cycles. The mechanical drive employs a toothed gearing system composed of an electric motor and meshing gear teeth.
Data collection was conducted using the central PV monitoring system, which logged DC output power, tracker motion events, and meteorological variables at 4-min intervals from sunrise to sunset. Pyranometers and temperature sensors were visually inspected and zero-adjusted according to manufacturer guidelines prior to the measurement campaign. Sensor readings were periodically cross-checked, and tracker alignment was verified at predefined timestamps to ensure accuracy and reliability of measurements.
The electrical characteristics of the PV modules at standard testing conditions (1000 W/m², 25 °C, AM1.5) are detailed in Table 4. Both monocrystalline and polycrystalline technologies adhere to the same manufacturer’s specifications for tracking and fixed systems.
In this section, we will evaluate four critical aspects of the performance of photovoltaic (PV) subfields: (I) Output Power, (II) Environmental Factors Influencing Performance, (III) Augmentation Percentage, and (IV) Daily Energy Yield. The primary objective of this assessment is to identify which PV subfield demonstrates the highest performance and is the most suitable for installation in regions with desert climatic conditions, such as the OUED-NECHOU region in Ghardaïa City.
To evaluate photovoltaic module performance, a simulation approach was conducted by Constance Kalu et al.⁴⁷. Using PVsyst version 5.21 and NASA meteorological data along with hypothetical load demand, the study compares polycrystalline, monocrystalline, and thin-film PV technologies. It finds that thin-film PV technology, despite its low array loss, low unit cost of energy, and favorable performance metrics, requires a larger installation area. In contrast, polycrystalline PV technology, with higher efficiency and smaller space requirements, is deemed more suitable for the specific site due to its superior efficiency and compact space needs. Furthermore, Allouhi et al.⁴⁵ assessed the performance, economic feasibility, and environmental impact of 2 kWp grid-connected PV systems (Poly-Si and Mono-Si) installed at the High School of Technology, Meknes, Morocco. The two PV fields are oriented south at a fixed tilt angle of 30°. Using METEONORM data and PVSYST simulations, the study found Poly-Si modules slightly outperform Mono-Si, with a higher annual average daily final yield. The Meknes systems perform better than those in Greece, Ireland, India, South Africa, and the UAE. Economically, Poly-Si has a lower levelized cost of electricity ($0.073/kWh) and shorter payback time (11.10 years) compared to Mono-Si ($0.082/kWh and 12.69 years). The systems also offer significant environmental benefits, reducing CO2 emissions by about 5.01 tons annually. The International Electrotechnical Commission (IEC) recommends several parameters for assessing PV power plant performance, as outlined in IEC-61724 standards. Key parameters include the final yield (Yf), reference yield (Yr), performance ratio (PR), and capacity factor (CF) Cubukcu & Gumus⁶⁵. Pirzadi & Ghadimi⁶⁶. Veerendra Kumar et al.⁶⁷. Ismail Bendaas et al.⁶⁸. Irfan Jamil et al.^{54,60,61,62,63,64,65,69}. These indicators are crucial for evaluating the efficiency and profitability of various PV power plants under different climatic conditions and for detecting potential issues or failures. Building on this. El Mehdi Karami et al.⁷⁰ evaluated the performance of grid-connected PV systems with monocrystalline, polycrystalline, and amorphous silicon modules in Casablanca, using 2016 data and PVsyst simulations. They assessed performance parameters such as annual energy generation, final yield, reference yield, performance ratio, and capacity factor. Results indicated that simulations were accurate for energy production and irradiation but less accurate for ambient temperature. Performance ratios were 76.94% for p-si, 78.02% for c-si, and 67.28% for a-si, with final yields of 4.61, 4.68, and 4.02 kWh/kWp/day, respectively. The study confirms PVsyst’s reliability but suggests using on-site temperature measurements for better simulation accuracy.
Assessing solar panel performance by analyzing output power, a critical electrical parameter, is essential for comparative studies, especially when considering the specific meteorological conditions of a given location. El Mehdi Karami et al.⁷⁰ conducted additional research to evaluate the performance of different solar panel technologies. They assessed the DC power output from the modules and the AC power from the inverters using real-time measurements under various weather conditions clear, cloudy, and rainy. Additionally, Layachi Zaghba et al.⁷¹ conducted an experimental study on an 11.28 kWp grid-connected solar system with sun tracking over one year at the Applied Research Unit of Renewable Energy in Ghardaia, Algeria. The study combines simulation data from PVSYST with experimental results and features three 3.76 kWp solar tracker configurations: fixed-axis, one-axis, and dual-axis. In a specific section, it compares the power output of single-axis and dual-axis trackers with fixed-axis systems under varying weather conditions, including clear and cloudy skies. Arechkik Ameur et al.⁷² aimed to analyze and compare various indices for evaluating the performance of three grid-connected photovoltaic technologies (a-Si, pc-Si, and mc-Si) in Ifrane, Morocco, et al. Akhawayn University. The study examines systems generating 2 kWp each, installed facing south on a flat surface, tilted at 32°, with zero azimuth. It evaluates AC power output under sunny and snowy conditions, considering the impact of temperature on power output.
Two different crystalline silicon photovoltaic technologies, monocrystalline silicon (mc-Si) and polycrystalline silicon (pc-Si), were evaluated using two types of support structures: fixed-axis and single-axis, both with a 30° tilt. Each PV subfield consisted of identical 100 kWp systems. Data were collected every 4 min in real-time through field measurements, as illustrated in Figs. 12, 13, 14, and 15. A comparative analysis was conducted. On the peak output power and long-term daily power generation for January 1^st, May 1^st, July 1^st, and October 1^st, representing the four seasons.
Comparison of output power (kW) between fixed and single-axis PV subfields for mc-Si and pc-Si on January 1^st, 2016. A winter day .
Comparison of output power (kW) between fixed and single-axis PV subfields for mc-Si and pc-Si on May 1^st, 2016. A spring day .
Comparison of output power (kW) between fixed and single-axis PV subfields for mc-Si and pc-Si on July 1^st, 2016. A summer day .
Comparison of output power (kW) between fixed and single-axis PV subfields for mc-Si and pc-Si on October 1^st, 2016. A fall day .
After confirming the accuracy of the PV subfields’ real performance data. Figure 12 shows the power output of the fixed-axis and one-axis mc-Si and pc-Si subfields on a winter’s day in January 1^st, 2016. Around 12:58 PM, the fixed mc-Si subfield reached its peak of 82.31 kW, the highest output of the day. Earlier, at 10:37 AM, the motorized mc-Si subfield produced 75.10 kW. Past midday the fixed pc-Si subfield generated 73.98 kW at 12:57 PM, while the motorized pc-Si recorded the lowest output of 73 kW at 10:50 AM.
The findings from the four PV subfields on May 1^st, 2016, a spring day, are displayed in Fig. 13. Showing the maximum power output recorded during the four-day pilot study. At 12:23 PM, the fixed mc-Si subfield achieved the highest power output ever recorded, approaching 95.67 kW.This was followed by the motorized mc-Si subfield, which produced 88.35 kW at 12:20 PM. At the same time, the fixed pc-Si subfield produced 84.06 kW, while the motorized pc-Si subfield recorded the lowest output of 83.01 kW at 14:40 PM.
Figure 14 illustrates the comparison of output power curves from four subfields one -axis and fixed-axis mc-Si and pc-Si using real data from July 1^st, a summer day. The experimental results on this day differed from those of the previous day. The one-axis mc-Si subfield yielded the highest power output on this day, producing 86.38 kW at 12:56 PM. This was followed by the fixed mc-Si subfield, which generated 83.84 kW at 12:46 PM. The motorized pc-Si subfield produced 76.84 kW at 13:28 PM, while the fixed pc-Si subfield achieved 71.12 kW.
Figure 15 presents experimental real data on output power for fixed-axis and one-axis PV subfields from October 1^st, 2016, covering a full day. The curves reveal that the fixed-axis mc-Si subfield yielded the highest output power compared to other subfields, achieving 88.00 kW at 12:56 PM. Following this, the one-axis mc-Si subfield delivered 78.79 kW at 13:05 PM. Additionally, the performance comparison between the fixed and single-axis pc-Si subfields shows a relatively close peak output, with the fixed pc-Si subfield achieving 76.88 kW and the single-axis pc-Si subfield reaching 73.06 kW at 10:50 AM.
When comparing the DC output power performance of four conventional PV subfields in this section, the results from four experimental days indicate that on each of these days, the power output of the solar panels was monitored from sunrise to sunset, between 06:00 AM and 19:52 PM. Among the subfields, the fixed monocrystalline (mc-Si) consistently generated the highest output power, with a peak value of 95.67 kWp recorded on May 1^st, close to the subfield’s optimal capacity. Additionally, on the same day, the single-axis monocrystalline (mc-Si) subfield demonstrated a peak output power of 88.35 kWp.
Notably, the single-axis solar tracker consistently increased the amount of power generated throughout all experimental days, from sunrise to sunset, by capturing more solar radiation compared to a fixed module. This effect was particularly evident on January 1^st, May 1^st, and July 1^st. As a result, by implementing single-axis tracking systems in our mc-Si and pc-Si subfields, the PV panels were able to continuously track the sun. These systems ensure that the panels remain optimally aligned with the sun throughout the day and across the year, maximizing the exposure of the panel’s surface. This alignment leads to increased conversion efficiency and, consequently, higher electricity generation (output power). Additionally, tracking systems optimize land area usage for electricity production compared to non-tracking systems, making them a more efficient choice. This finding is consistent with those obtained by many authors who have studied solar tracking systems. Hafez et al.⁷³ introduced an innovative solar single-axis tracking system powered by a Stirling engine, which was used to evaluate the performance of solar panels in Giza, Egypt. The East–West axis system achieved higher output power than the fixed system. Research carried out by Layali Abu Hussein et al.⁷⁴ in Amman, Jordan, looked into the performance improvement of standard fixed photovoltaic (PV) solar systems by using single and dual-axis sun tracking mechanisms. They compared these systems to concentrated photovoltaic (CPV) systems, which inherently use tracking systems. The study included an experimental analysis, characterization, and performance comparison of four mounting types of standard PV systems. The PV panels were installed using either a fixed mount, single-axis (East–West tracking), single-axis (North–South tracking), or dual-axis tracking. The study’s findings confirmed that electrical power generation on tracking surfaces was significantly higher than on a fixed surface. Additionally, the study demonstrated that both East–West and North–South tracking systems produced more power compared to a fixed surface inclined at 26° to the south.
Climatic, environmental, and operational conditions, along with geographical locations, play a crucial role in the energy yield of photovoltaic (PV) systems. This concept has driven research focused on quantifying and modeling the output power of PV systems under diverse conditions. Researchers globally aim to understand better how these parameters affect PV system performance. According to Elkholy et al.⁷⁵, reduced solar irradiation significantly influences the energy quality produced by photovoltaic systems.Dabou et al.⁷⁶, conducted a study examining the impact of climatic conditions on the performance of grid-connected photovoltaic systems. The findings indicate that performance is influenced on cloudy and sandy days due to the rapid and successive changes in cloud cover and sand exposure, which affect both the energy output and the stability of the photovoltaic system. In their 2014 study, Panagea et al.⁷⁷ discovered a clear inverse link between PV power and temperature in Greece. They also observed that as irradiance intensity rises, so does PV power. As reported by Schwingshackl et al.⁷⁸ and Kaplani and Kaplanis⁷⁹, wind speed significantly enhances PV performance by cooling the PV surfaces, which in turn reduces the parallel resistance within the PV circuit model. Humidity decreases PV output by diminishing the amount of solar irradiance received. Nevertheless, when combined with wind speed, humidity significantly contributes to cooling PV surfaces, thereby enhancing PV efficiency in hot climates Zainuddin et al.⁸⁰.
Currently, no published studies provide experimental results on the performance of photovoltaic systems and their interaction with environmental factors in the OUED-NECHOU region, Ghardaïa. This section presents a comparative analysis of the influence of meteorological parameters on photovoltaic subfield performance based on experimental data. The study evaluates the effects of solar irradiance at a 30° tilt, cell irradiation at the same angle, ambient temperature, cell temperature, relative humidity (Fig. 2), and wind speed (Fig. 3) on the DC power output. Furthermore, the performance of both fixed and motorized (single-axis) subfields is analyzed to determine which technology is more effective under these environmental conditions. Real-time meteorological data was collected using sensors installed at a weather station (Table 1) on the roof of the control room, recorded at four-minute intervals on January 1^st, May 1^st, July 1^st, and October 1^st each representing a different season. The data was displayed and analyzed, as shown in Figs. 2, 3, 16, and 17.
Daily experimental data of average ambient temperature (°C) and module temperature (°C) over four days, each corresponding to a different season.
Daily experimental data of average inclined solar irradiance (W/m²) and calibrated cell radiation (W/m²) for four subfields over four days, measured at a 30° tilt angle.
Figure 16 compares experimental data from four days, including ambient temperature recorded by a thermo-hygrometer installed at the weather station and PV module temperature from both fixed and motorized technologies, measured by cell sensors installed in the subfields. Data analysis revealed that ambient temperatures consistently exceeded the temperatures recorded by the PV cell sensors throughout the four experimental days. PV module temperatures also increased with rising ambient temperatures, with the most significant effect observed on July 1^st.
The fixed mc-Si technology reached its peak panel surface temperature of 33.16 °C on July 1^st and its lowest of 23.02 °C on May 1^st, while the fixed pc-Si PV technology recorded its highest at 32.19 °C on May 1st and its lowest at 21.21 °C on January 1^st. These distinct temperature changes vividly illustrate the seasonal performance variations of these PV technologies. On July 1^st, mc-Si and pc-Si one-axis panels recorded their maximum average temperatures of 27.88 °C and 31.39 °C, respectively, while on January 1^st, they had their minimum averages at 18.49 °C and 21.92 °C.
Figure 17 showcases an experimental comparison of inclined solar irradiance (W/m²) recorded by a pyranometer and measured by calibrated cells, both positioned at a 30° tilt angle over four days representing different seasons.
Significant emphasis was placed on the clear and qualitative response of the subfields to different levels of solar radiation. The motorized mc-Si and pc-Si subfields outperformed the fixed subfields and the pyranometer in capturing solar radiation.
On July 1^st, a summer day, the monocrystalline silicon (mc-Si) technology recorded a peak average solar irradiance of 782.51 W/m², the highest observed during the study. In contrast, the lowest value, 504.11 W/m², was recorded on October 1^st, a fall day. On January 1^st, a winter day, the irradiance was 730.94 W/m², while on May 1^st, a spring day, it was 508.41 W/m². The motorized pc-Si subfield also achieved significant irradiance values, with a maximum average of 627.21 W/m² on July 1^st. On May 1^st, it recorded 576.68 W/m². During winter (January 1^st) and fall (October 1^st), the irradiance values were 502.77 W/m² and 449.67 W/m², respectively.
On May 1^st, the pyranometer recorded a maximum average solar irradiance of 651.16 W/m². The fixed mc-Si sub-field recorded an average irradiance of 560.58 W/m², which is 90.58 W/m² lower than the pyranometer’s measurement. The fixed pc-Si subfield recorded a maximum irradiance of 550.58 W/m², showing a difference of 100.58 W/m² from the pyranometer’s reading. In October, the pyranometer recorded the lowest tilted solar irradiance values in this study, with a minimum of 442.03 W/m². The fixed mc-Si subfield measured 428.61 W/m², 13.42 W/m² lower than the pyranometer’s reading, while the fixed pc-Si subfield recorded 422.61 W/m², 19.42 W/m² below the pyranometer’s measurement.
These measurements illustrate the variability in irradiance captured by different PV technologies, highlighting the pyranometer’s role as a benchmark for evaluating the performance of photovoltaic subfields in capturing solar radiation.
The experimental results indicate that one-axis solar subfields consistently generate more power from sunrise to sunset compared to fixed subfields. This increased power production was particularly evident on January 1^st, May 1^st, and July 1^st. The east–west alignment of single-axis panels optimizes solar energy absorption by optimizing the polarization angle of incoming solar radiation.
Natural factors clearly influence this variation in power production. Extensive studies have proven this, including those by Karami et al.²⁷. Al-Otaibi et al.⁴⁹, and Moafaq et al.⁸¹. Layali Abu Hussein et al.⁷⁴. At the OUED-NECHOU station, the tilt angle of the solar panels plays a crucial role in determining photovoltaic subfield efficiency. A well-adjusted tilt that aligns closely with the region’s optimal angle improves solar energy absorption and enhances power generation. Observations on May 1st and July 1^st revealed that single-axis subfields benefited the most from increased solar irradiance, resulting in notable power gains⁷⁴. On July 1^st, the motorized panels recorded peak solar radiation values of 782.51 W/m² for mc-Si and 625.51 W/m² for pc-Si, highlighting their ability to maximize power generation compared to fixed panels. During the experimental study, the average temperatures of the photovoltaic (PV) technologies remained close to the optimal Standard Test Condition (STC) of 25 °C, occasionally exceeding this temperature. Notably, on July 1^st, higher temperatures contributed to significant DC power generation, indicating favorable conditions for efficient operation. Despite the increase in temperature, power output rose, with the single-axis subfields achieving more significant gains than the fixed subfields. It suggests that elevated temperatures did not hinder performance but enhanced productivity. On July 1^st, conditions were particularly advantageous for both fixed and motorized panels, leading to higher energy yields. A similar trend was observed on May 1^st, where rising temperatures also correlated with increased power output. The recorded average temperatures on these days remained within the optimal range for solar panel performance. High temperatures negatively affect the performance of solar panels, as they reduce their efficiency and power output. The evidence for this previous study conducted in Southeast China by Du et al.⁸² showed that temperatures above 60 °C significantly reduce panel power output while lowering the temperature below this threshold increases efficiency and power generation. The panels operated near their optimal capacity since such extreme temperatures were not observed in our experimental study. Since rising temperatures adversely affect the performance of solar panels, finding practical solutions to alleviate this impact is crucial. Researchers such as Mohamed R. Gomaa et al.⁴⁴, their study experimentally evaluated two cost-effective cooling methods to enhance PV system performance: direct active cooling using water and passive cooling with fins. A non-cooled PV module was used as a reference for comparison. The findings showed that the water cooling method reduced the module surface temperature to 38 °C, while the fin cooling method brought it down to 55 °C, compared to 58 °C for the non-cooled module. These cooling techniques enhanced energy performance, resulting in a 10.2% increase in daily harvested energy for the water-cooled module and a 7% increase for the fin-cooled module. Additionally, the performance ratio improved to 84% with water cooling and 81% with fins, while the non-cooled module had a performance ratio of 77%.
Furthermore, wind speed and humidity significantly impact the efficiency of photovoltaic subfields. During the experimental period, we observed that higher wind speeds and lower humidity levels improved solar panels output. Increased airflow effectively reduced localized humidity on May 1^st and July 1^st by promoting continuous air movement over the panels. It led to increased power generation. Additionally, motorized subfields outperformed fixed subfields due to the cooling effect of wind, lower atmospheric moisture, and better solar absorption, resulting in consistently superior performance. Our experimental analysis confirmed an inverse relationship between wind speed and relative humidity: as wind speed increased, humidity levels decreased, further supporting these findings. Water condensation on solar panels can decrease their efficiency by causing moisture build-up. To address this issue, we optimize the tilt angle in our subfields, where photovoltaic panels are installed at a fixed tilt of 30° which allows water droplets to run off rather than accumulate, thus minimizing prolonged moisture exposure. Additionally, natural airflow in well-ventilated areas enhances this effect. On May 1^st and July 1^st, increased airflow effectively reduced localized humidity by promoting continuous air movement over the panels. This led to higher power gains for the single-axis tracking system and improved overall power generation.
These observations reinforce the idea that a single meteorological factor does not determine a photovoltaic system’s ability to convert solar radiation into electrical energy; rather, it is the combined influence of irradiance, temperature, wind speed, humidity, and panel orientation. Under favorable conditions- high irradiance, moderate temperatures, enhanced airflow, and reduced surface moisture—the panels can absorb a greater portion of incoming solar energy, resulting in higher conversion efficiency and improved power output. In particular, single-axis tracking systems show a stronger response to these favorable environmental conditions, as their continuous orientation toward the sun maximizes capture of direct beam radiation while also enhancing natural cooling through increased exposure to wind. This synergistic interaction among optimal tilt alignment, improved heat dissipation, reduced moisture accumulation, and maximum irradiance collection significantly contributes to the superior performance of single-axis tracking subfields compared to fixed systems in desert environments such as OUED-NECHOU.
In regions like OUED-NECHOU, which are generally hot and dry but can occasionally experience localized humidity, additional measures can further optimize PV performance. Installing small fans or passive ventilation systems activated by humidity sensors can help remove water droplets from the panel surface while keeping energy consumption minimal. This approach ensures efficient panel operation without compromising energy production, particularly for single-axis systems designed to capture maximum solar radiation. By combining these environmental insights with practical mitigation strategies, PV systems can maintain higher efficiency and more stable power output under varying desert conditions.
The concept of “Augmentation Percentage” in the realm of renewable energy, particularly photovoltaic technologies, denotes the relative enhancement in the performance of a specific technology or system compared to a reference or baseline technology. This metric is determined by calculating the percentage increase or decrease in a particular performance indicator (e.g., power output or efficiency) of the new or alternative technology relative to the baseline⁴⁶.
Baseline Technology: This term refers to the standard or reference photovoltaic (PV) technology or system used as a starting point for comparison. It signifies the most prevalent, widely used, or preferred technology in your study.
The percentage of augmentation would be calculated as follows:
AP: Augmentation percentage (%).
P_baseline: Mean output power (KW) of the baseline (reference) technology or subfield.
P_new : Mean output power (KW)of the new technology or subfield.
The performance improvement of two single-axis tracking sub-fields was evaluated in comparison to two fixed photovoltaic sub-fields during a four-day experimental period in 2016, with each day representing a different season. Monocrystalline (mc-Si) and polycrystalline (pc-Si) silicon technologies were used. Mean output power was measured for both subfield types, and the percentage of augmentation was calculated to quantify the performance gains.
Data from January 1^st, 2016, shown in Fig. 18. Illustrates the increase in mean output power (in kW) for single-axis tracking systems compared to fixed systems for mc-Si and pc-Si sub-fields. The single-axis tracking sub-fields served as baseline technologies for comparison. The mc-Si single-axis tracking system achieved a mean output power of 57.060 kW, representing a 3.263% increase over the fixed sub-field output of 55.198 kW. Similarly, the pc-Si single-axis tracking system generated 55.318 kW, resulting in an 11.849% increase compared to the fixed sub-field output of 48.763 kW.
Percentage increase in mean output power for fixed and single-axis tracking subfields (mc-Si, pc-Si) on January 1^st, 2016 (winter day).
In Fig. 19 the results of an experiment conducted on May 1^st, 2016 are presented. The experiment aimed to compare the mean output power of fixed and single-axis tracking systems for mc-Si and pc-Si sub-fields during the Spring .The results show that the single-axis tracking subfield, designated as baseline I for mc-Si and baseline II for pc-Si, significantly outperformed the fixed systems. Specifically, the mc-Si single-axis tracking system achieved a mean output power of 57.710 kW, representing a 9.979% increase over the fixed system’s output of 51.451 kW. Similarly, the pc-Si single-axis tracking system generated 56.940 kW, resulting in a 20.226% increase compared to the fixed system’s output of 45.423 kW.
Percentage increase in mean output power for fixed and single-axis tracking subfields (mc-Si, pc-Si) on May 1^st, 2016 (spring day).
Figure 20 presents data on the percentage increase in mean output power (in kW) for single-axis tracking and fixed systems using mc-Si and pc-Si subfields on July 1^st, a summer day. The mc-Si single-axis tracking system, considered as Baseline I, achieved a mean output power of 60.470 kW, representing a 19.221% increase over the fixed system’s output of 48.847 kW. Similarly, the pc-Si single-axis tracking system, established as Baseline II, generated 54.864 kW, resulting in a 21.444% increase compared to the fixed system’s output of 42.550 kW.
Percentage increase in mean output power for fixed and single-axis tracking subfields (mc-Si, pc-Si) on July 1^st, 2016 (spring Day).
On October 1^st, on a fall day, Fig. 21 depicts the percentage increase in average output power (in kW) for single-axis tracking and fixed systems using mc-Si and pc-Si subfields. The single-axis tracking systems are referred to as Baseline I for the mc-Si sub-field and Baseline II for the pc-Si sub-field. The mc-Si single-axis tracking system achieved a mean output power of 48.600 kW, representing a 9.362% increase over the fixed system’s output of 44.050 kW. Similarly, the pc-Si single-axis tracking system generated 45.134 kW, resulting in an 11.791% increase compared to the fixed system’s output of 39.812 kW.
Percentage increase in mean output power for fixed and single-axis tracking subfields (mc-Si, pc-Si) on October 1^st, 2016 (spring day).
The empirical data clearly demonstrates that single-axis tracking systems lead to a substantial increase in the daily average power output (kW) for both mc-Si and pc-Si subfields compared to fixed subfields. This underscores the crucial role of tracking mechanisms in enhancing subfield performance, especially in regions with high solar radiation, diverse sun paths, and favorable weather conditions.
All photovoltaic (PV) subfields have the same power capacity, with a rated instantaneous output of 100 kW. Figure 22 displays the results of a comparative experimental analysis of daily energy production between fixed and single-axis tracking subfields ,conducted over four days, each representing a different season. This study investigates how solar irradiance influences energy variations, emphasizing its role in enhancing productivity in photovoltaic subfields, particularly when utilizing a mechanical tracking system. To ensure accuracy and reliability, energy generation data was recorded at four-minute intervals throughout the daily measurement period.
Comparison of daily energy generation in fixed and single-axis tracking PV subfields across four experimental days.
On January 1^st, in winter, the single-axis mc-Si subfield recorded the highest energy output at 547.73 kWh/day, followed by the single-axis pc-Si system, which yielded 531.05 kWh/day. In comparison, the fixed mc-Si system generated 529.92 kWh/day, while the fixed pc-Si subfield produced the least energy at 468.14 kWh/day. The overall low energy production observed on January 1^st can be attributed to the weak solar radiation and the shorter duration of daylight typical of winter.
The data recorded on May 1^st highlights the seasonal effects on energy production. During the spring season, energy production saw a significant increase due to the transitional seasonal conditions. The mc-Si single-axis system achieved a peak output of 750.24 kWh/day, while the pc-Si single-axis subfield generated 646.85 kWh/day. The fixed mc-Si configuration also performed well, producing 671.50 kWh/day, whereas the fixed pc-Si system generated 590.50 kWh/day.
The highest recorded energy output was observed on July 1^st, during the summer season. The mc-Si single-axis subfield achieved its peak generation, producing 787.94 kWh/day, while the pc-Si single-axis system closely followed with 715.17 kWh/day. Among the fixed systems, the mc-Si subfield generated 636.15 kWh/day, whereas the pc-Si fixed system recorded the lowest output for this period at 553.43 kWh/day. This notable increase in performance is attributed to extended daylight hours and higher irradiance levels during the summer.
As fall began on October 1^st, a decline in energy generation was observed. The mc-Si single-axis subfield led the performance with an output of 550.77 kWh/day, followed by the pc-Si single-axis system, which generated 511.52 kWh/day. The fixed mc-Si system produced 498.17 kWh/day, while the fixed pc-Si subfield had the lowest recorded energy output for this period, generating only 451.21 kWh/day.
The superior energy yield of motorized subfields is attributed to their ability to continuously track the sun’s position throughout the day, maximizing the capture of solar irradiance. This dynamic orientation reduces angle losses and ensures that the photovoltaic (PV) modules receive optimal sunlight exposure, particularly during the early morning and late afternoon when fixed systems tend to exhibit lower efficiency. Additionally, optimizing the mechanical tilt of solar panels enhances direct irradiance absorption, thereby increasing energy generation. These findings highlighted the benefits of single-axis tracking technology, particularly in regions with high solar potential, where seasonal variations can greatly affect photovoltaic efficiency.
Despite its valuable contributions to understanding the performance of fixed and single-axis PV systems under real desert conditions, this study has certain limitations. The experimental analysis was limited to four days representing different seasons, providing representative seasonal insights but not capturing long-term year-round variability or extreme meteorological conditions. The results are site-specific to the OUED-NECHOU region in Ghardaïa, characterized by Saharan climatic conditions with high solar irradiance and notable variations in ambient temperature, wind intensity, and humidity; therefore, the findings may not be directly generalizable to regions with different environmental or irradiance profiles. Furthermore, the study focused exclusively on crystalline silicon technologies—monocrystalliene (mc-Si) and polycrystalline (pc-Si)—without considering other photovoltaic technologies, such as thin-film or bifacial modules, which may behave differently under similar conditions. Future research should extend the monitoring period, include additional PV technologies, and integrate economic and degradation analyses to provide a more comprehensive understanding of PV system performance and sustainability. These aspects will be addressed in forthcoming studies to strengthen the findings further.
This study systematically compared the performance of four photovoltaic (PV) subfields monocrystalline (mc-Si) and polycrystalline (pc-Si) -in fixed and single-axis tracking (East–West) configurations, each with a 30° tilt and 100 kWp capacity. Performance was analyzed over four days representing different seasons under varying meteorological conditions to determine the most effective configuration.
The semi-empirical PERRIN DE BRICHAMBAUT model was used to forecast solar flux on the 30° inclined surface in real time. Statistical analysis demonstrated high model accuracy, with correlation coefficients (CC) between 0.8273–0.9668, RMSE of 4.27–7.72 W/m², MAE of 52.27–65.94 W/m², and MAPE of 1.97–8.87%. The small absolute error across most days confirmed that the model closely predicted actual measurements, indicating it can reliably estimate inclined solar irradiance in OUED-NECHOU and similar Saharan regions even in the absence of a meteorological station.
Daily output power data showed that May 1^st recorded the highest peak outputs. The fixed mc-Si system reached 95.57 kW, followed by the mc-Si single-axis system at 88.35 kW , the fixed pc-Si subfield at 84.06 kW, and the pc-Si single-axis system at 83.01 kW. Average daily production revealed peak outputs of 60.47 kW (single-axis mc-Si, July 1^st ), 55.20 kW (fixed mc-Si, January 1^st ), and 56.94 kW (single-axis pc-Si, May 1^st ), with 48.76 kW for the same subfield on January 1^st.
The analysis of four days of experimental data revealed a strong correlation between meteorological factors—including solar irradiance, cell and ambient temperatures, wind speed, and relative humidity—and PV power output. Higher irradiance levels directly increased power generation, especially in crystalline silicon modules, which showed strong responsiveness to irradiance variations. For instance, the mc-Si single-axis system reached irradiance peaks of 782.51 W/m² on July 1^st and 730 W/m² on May 1^st, resulting in corresponding rises in power output. The superior performance of the single-axis system is attributed to its motorized tracking mechanism, which continuously aligns the panels with the sun’s east–west movement, ensuring optimal solar capture.
PV performance was also influenced by temperature: efficiency remained high within the optimal range around 25 °C, while excessive heat slightly reduced output voltage. On July 1^st, the highest average temperature coincided with the greatest power gain in single-axis systems, confirming that temperature played a favorable role under these conditions. Moreover, higher wind speeds and lower humidity on May 1st and July 1st enhanced power generation by cooling the cells, whereas low wind and high humidity on January 1st and October 1st reduced performance due to cloud cover and water condensation on panel surfaces that limited irradiance absorption.
Tracking systems consistently enhanced photovoltaic performance compared to fixed installations. Both monocrystalline (mc-Si) and polycrystalline (pc-Si) single-axis subfields delivered higher power outputs across all experimental days, with the greatest gains observed on July 1^st and May 1^st. On these dates, the mc-Si tracker generated 19.22% and 9.98% more power gain than its fixed counterpart, while the pc-Si tracker produced 21.44% and 20.23% more than fixed pc-Si subfield, respectively. The lowest gains occurred on January 1^st for mc-Si (3.263%) and on October 1^st for pc-Si (11.791%).
The analysis confirmed the superior performance of single-axis tracking systems in energy production. On May 1^st, they generated 750.24 kWh/day for mc-Si and 646.85 kWh/day for pc-Si, while on July 1st, the outputs reached 787.94 kWh/day and 715.17 kWh/day, respectively. In contrast, fixed systems produced lower values of 671.50 kWh/day and 590.50 kWh/day on May 1^st, and 636.15 kWh/day and 553.43 kWh/day on July 1^st. These results highlight the effectiveness of tracking mechanisms in maximizing solar energy capture. Overall, the single-axis polycrystalline subfield exhibited slightly higher power gains than the monocrystalline one, while the mc-Si single-axis configuration showed the best overall efficiency in energy production. Therefore, implementing polycrystalline technology is recommended for the OUED-NECHOU region and similar Saharan environments due to its strong adaptability to local conditions.
Future improvements should focus on optimizing tilt angles and integrating adaptive control algorithms to enhance energy yield. Regular monitoring of photovoltaic (PV) panels is essential, particularly for single-axis tracking systems in dust-prone regions such as OUED-NECHOU. Beyond these practical enhancements, broader research should explore the development of climate-resilient, intelligent tracking systems suited to harsh desert environments. Kumba et al.¹⁸ provide a comprehensive review of solar tracking systems, discussing key operational and environmental challenges as well as future research directions, including optimization of mechanical architectures and adaptive control strategies. Likewise, Ponce-Jara et al.²⁰ demonstrated that single-axis tracking can substantially increase daily and long-term energy yield, although performance is influenced by local irradiance and climatic conditions.
Consistent with these findings, our experimental results in OUED-NECHOU confirmed that motorized single-axis tracking systems significantly enhance daily power production and energy generation across all seasons. Therefore, future studies should incorporate adaptive intelligent controllers, real-time environmental monitoring, predictive maintenance strategies, and alternative performance indicators to further optimize system efficiency, resilience, and durability under desert climatic conditions.
In addition to performance improvements, future research should evaluate the economic viability of single-axis tracking systems in the regional context. Recent techno-economic analyses Gol & Ščasný⁸³ show that one-axis trackers produce 20–30% more energy than fixed systems and achieve a lower LCOE. Demirdelen et al.⁸⁴ demonstrated that in Mediterranean climates, tracking systems offer significantly faster payback compared to fixed installations. Furthermore, Ayadi et al.⁸⁵ reported that in desert conditions, bifacial 1-axis tracking configurations can achieve a competitive LCOE of as low as ~ 2.45 ¢/kWh under favorable circumstances. Building on these insights, we plan to conduct a long-term, region-specific techno-economic assessment for OUED-NECHOU, including LCOE modeling, life-cycle costing, and maintenance cost projections. By integrating both performance and economic perspectives, future research will contribute to designing optimized, reliable, and cost-effective PV systems tailored to challenging desert environments like OUED-NECHOU.
The datasets used and/or analyzed during the current study are available from the corresponding author upon reasonable request.
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The authors would like to acknowledge the Deanship of Graduate Studies and Scientific Research, Taif University for funding this work.
This work is funded and supported by the Deanship of Graduate Studies and Scientific Research, Taif University.
Laboratory of Electrical Engineering (LAGE), Department of Electrical Engineering, University of Kasdi Merbah Ouargla, 30000, Ouargla, Algeria
Bouramdane Abderraouf, Louazene Mohammed Lakhdar, Benmir Abdelkader & Larouci Benyekhlef
Department of Electrical Engineering, University Kasdi Merbah Ouargla, Ouargla, Algeria
Larouci Benyekhlef
Smart Grid Development Laboratory, ESGEEO, Oran, Algeria
Larouci Benyekhlef
Department of Electrical Engineering, College of Engineering, Taif University, 21944, Taif, Saudi Arabia
Salah K. Elsayed & Abdulrahman Babqi
Department of Electrical and Computer Engineering, Faculty of Technology, Debre Markos University, P. BOX 269, Debre Markos, Ethiopia
Daniel Limenew Meheretie
Electrical Department, Faculty of Technology and Education, Suez University, Suez, 43527, Egypt
Walid S. E. Abdellatif
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Bouramdane Abderraouf, Louazene Mohammed Lakhdar, Benmir Abdelkader, Larouci Benyekhlef: Conceptualization, Methodology, Software, Visualization, Investigation, Writing- Original draft preparation. Salah K. Elsayed, Abdulrahman Babqi, Daniel Limenew Meheretie, Walid S. E. Abdellatif: Data curation, Validation, Supervision, Resources, Writing—Review & Editing, Project administration, Funding Acquisition.
Correspondence to Bouramdane Abderraouf or Daniel Limenew Meheretie.
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Abderraouf, B., Lakhdar, L.M., Abdelkader, B. et al. Experimental performance comparison of fixed and single-axis subfields in a large-scale outdoor photovoltaic power plant. Sci Rep 16, 12293 (2026). https://doi.org/10.1038/s41598-026-41570-8
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Received: 01 June 2025
Accepted: 20 February 2026
Published: 05 March 2026
Version of record: 14 April 2026
DOI: https://doi.org/10.1038/s41598-026-41570-8
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