The U.S. community solar sector reached a historic milestone in late 2025, officially surpassing 10 GWDC of cumulative national installations, according to a new report released by Wood Mackenzie in collaboration with the Coalition for Community Solar Access (CCSA). While the market experienced a 25% contraction in 2025 due to a slowdown in mature markets…
Session Recap and Price Action The stock opened with a 2.79% gap up and climbed steadily to an intraday high of Rs 247.35, closing near its peak. This performance marks a 9.39% gain over the past four sessions and a remarkable 30.27% rise year-to-date, while the Sensex has declined 8.22% over the same period. Emmvee Photovoltaic Power Ltd is trading comfortably above all key moving averages — 5-day, 20-day, 50-day, 100-day, and 200-day — signalling a sustained upward trend. The Electric Equipment sector itself gained 2.03% on the day, but Emmvee outperformed even this robust sector rally. Does this price momentum suggest a durable breakout or a short-term spike? Technical Indicators Show Mildly Bullish Signals The technical landscape for Emmvee Photovoltaic Power Ltd is mildly bullish. Bollinger Bands indicate upward momentum, and Dow Theory supports a positive trend, though RSI and OBV currently show no clear signals. The stock’s immediate support lies at Rs 171.50, its 52-week low, while resistance near Rs 222.65 (20-day moving average) has been decisively breached. The 52-week high of Rs 248.35 now acts as a psychological barrier, which the stock has just surpassed. Delivery volumes have surged, with a 46.37% increase over the past month and a 45.49% jump on the day, suggesting strong investor participation. How sustainable is this technical momentum given the mixed signals from key indicators? Rising fast and still accelerating! This Small Cap from FMCG sector is riding pure momentum right now. Jump in before the rally reaches its peak! Jump In Before It Peaks → Valuation Multiples Reflect Elevated Pricing At Rs 250.50, Emmvee Photovoltaic Power Ltd trades at a price-to-earnings (P/E) ratio of 21x, which is moderate but accompanied by a notably high price-to-book value (P/BV) of 17.20x. Enterprise value multiples are also elevated, with EV/EBITDA at 25.22x and EV/EBIT at 32.17x, while EV/Sales stands at 7.80x. These figures suggest that the market is pricing in significant growth expectations, despite recent financial headwinds. The absence of dividend payouts further concentrates returns on capital appreciation. At these valuations, should you be booking profits on Emmvee Photovoltaic Power Ltd or can the company grow into this premium? Financial Trend Shows Recent Weakness Contrasting the strong price action, the latest quarterly financials reveal a negative trend. The company reported a 74.4% decline in PAT to ₹14.17 crores compared to the previous four-quarter average. Net sales dropped to ₹81.07 crores, the lowest in recent quarters, while operating profit to interest coverage deteriorated to -5.62 times, signalling strained core profitability. The operating profit margin also contracted sharply to -8.18%. Notably, non-operating income accounted for 166.92% of profit before tax, indicating reliance on non-core sources to offset operational losses. This disconnect between financial performance and market valuation raises questions about the sustainability of the rally. Is this divergence between price and fundamentals a warning sign or a temporary anomaly? Quality Metrics Highlight Strengths and Weaknesses From a quality perspective, Emmvee Photovoltaic Power Ltd exhibits a mixed profile. The company boasts a strong average return on capital employed (ROCE) of 20.91%, reflecting efficient capital utilisation. Management risk is assessed as average, and capital structure is considered good, with low net debt to equity and no promoter share pledging. However, growth metrics over five years show no increase in sales or EBIT, and average EBIT to interest coverage is weak at 2.69x, indicating some financial vulnerability. Institutional holdings stand at a moderate 14.74%, which may influence liquidity and price stability. How do these quality factors balance against the stretched valuations and recent financial setbacks? Holding Emmvee Photovoltaic Power Ltd from Other Electrical Equipment? See if there’s a smarter choice! SwitchER compares it with peers and suggests superior options across market caps and sectors! Switch to Better Options → Key Data at a Glance Balancing Bull and Bear Cases The rally in Emmvee Photovoltaic Power Ltd is underpinned by strong technical momentum and a clear outperformance relative to the Sensex and sector peers. However, the stretched valuation multiples and recent quarterly financial weakness introduce a note of caution. The elevated P/B ratio and high EV multiples suggest the market is pricing in a turnaround that has yet to materialise in the numbers. Meanwhile, the strong ROCE and absence of promoter pledging provide some reassurance on capital efficiency and governance. Should you buy, sell, or hold? With momentum and valuations pulling in opposite directions, no single data point tells the full story — see the complete multi-factor analysis of Emmvee Photovoltaic Power Ltd to find out. Summary Emmvee Photovoltaic Power Ltd has achieved a significant milestone by reaching an all-time high near Rs 250.50, fuelled by a strong price rally and positive technical signals. Yet, the recent quarterly results reveal a sharp decline in profitability and sales, contrasting with the market’s optimistic pricing. Investors should weigh the robust capital efficiency and technical strength against the stretched valuations and financial softness before making decisions. The coming quarters will be critical in determining whether the company can translate its market momentum into sustained earnings growth. Limited Period Only. 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Thank you for visiting nature.com. You are using a browser version with limited support for CSS. To obtain the best experience, we recommend you use a more up to date browser (or turn off compatibility mode in Internet Explorer). In the meantime, to ensure continued support, we are displaying the site without styles and JavaScript. Advertisement Energy transition Nature Energy (2026)Cite this article When households install rooftop solar panels, they often increase their electricity consumption due to the perception of ‘free’ energy, a phenomenon known as the solar rebound effect. Energy scenarios should reflect this additional demand, while associated policy should incentivize use during sunny hours to limit system costs and unfair cost shifting. Incorporating the solar rebound effect into official system planning may help ensure energy infrastructure is designed for realistic demand. The solar rebound effect should not be treated as a fixed increase in demand, as its timing varies across hours and seasons and can substantially change infrastructure needs, system costs, and planning outcomes. Tariffs and incentives that encourage rooftop solar PV households to shift flexible consumption to sunny hours can reduce system impacts, since rebound demand is least costly when it coincides with solar generation and more costly when it occurs in low-solar hours. The solar rebound effect can shift system costs onto other electricity consumers without PV, creating regressive impacts as solar rollout increases, highlighting the need to quantify and monitor distributional effects. You have full access to this article via your institution. based on Delic, M. & Bucksteeg, M. Implications of the solar rebound effect for the European energy transition. Nat. Energyhttps://doi.org/10.1038/s41560-026-02031-8 (2026) Rooftop photovoltaics (PV) are a cornerstone of Europe’s energy transition. However, their success may be undermined by the solar rebound effect (SRE), where PV owners may consume more electricity after installation because their solar power is essentially free to use. Current abatement scenarios and simulation studies fail to account for the additional electricity consumption induced by this effect, leaving an important blind spot in energy system planning. While empirical studies have repeatedly confirmed the SRE, robust evidence on its system-wide implications remains limited. Millions of households using rooftop solar may increase their electricity consumption, and depending on where the rebound effect occurs, this may trigger additional infrastructure investments and raise overall system costs. Such costs must be recovered through higher electricity tariffs, which raises distributional concerns given that solar households benefit while the costs are also borne by households that can’t afford PV. Our analysis reveals that the SRE may increase electricity demand by 63–314 TWh by 2050, increasing Europe’s total demand by up to 5.1% in the worst-case scenario (Fig. 1c). Meeting this extra demand requires additional renewable generation and grid flexibility, increasing annual total power-system costs by €6.7–23.5 billion per year between 2030 and 2050 (up to 4.2% in 2050; Fig. 1d). If consumption rises mainly during sunny hours, the system can absorb increased demand at a lower cost. However, if rebound demand shifts into evenings and winter periods, it triggers higher needs for wind generation, batteries, and costly long-duration backup such as hydrogen, substantially increasing system costs and electricity prices. Finally, the SRE has a regressive impact, with system costs passed through to higher electricity prices that disproportionately affect non-PV adopters, unless current tariff structures are changed. Springer Nature Limited a, PV generation profile (typical day) and schematic rebound demand profiles representing three rebound demand profiles: dynamic (time-shifted), simultaneous (coincident with PV generation), and sweeping (evenly distributed). b, Reference household electricity demand (typical weekday) and the corresponding load shapes under the same three rebound demand profiles. c, Total electricity demand (TWh yr−1) for the reference scenario and the maximum SRE case; coloured points indicate other SRE effect–strength/timing combinations; labels report the absolute value for the maximum SRE case and the percentage change relative to the reference. d, Annual total system costs (bn€ yr−1) for the reference scenario and the maximum SRE case; points and labels as in c. Figure adapted from Delic, M. & Bucksteeg, M. Nat. Energyhttps://doi.org/10.1038/s41560-026-02031-8 (2026). We integrate empirically observed SRE intensities and profiles from scientific literature into an open-source energy system model covering power, heat, transport, and hydrogen sectors. The model chooses a least-cost mix of generation and storage to meet hourly demand while following a Paris Agreement-aligned path to climate neutrality by 2045. We simulate 34 European market areas from 2030 to 2050 in five-year steps and compare a baseline run without rebound to scenarios with low (7.7%), average (17.2%), and high (33%) rebound intensity. Because the timing of additional consumption is uncertain, we implement three different rebound demand profiles (see Fig. 1a, b): (simultaneous) concentrated around midday solar output, (sweeping) evenly distributed across the day, and (dynamic) capturing both immediate increases during sunny hours and systematic shifts of additional consumption into evening periods with seasonal variation. Galvin, R. et al. A health research interdisciplinary approach for energy studies: confirming substantial rebound effects among solar photovoltaic households in Germany. Energy Res. Soc. Sci.86, 102429 (2022). This article confirms that the solar rebound effect is a persistent behavioral phenomenon, driven by perceptions of ‘free’ energy. Article Google Scholar Bigler, P. Magnitude and decomposition of the solar rebound: evidence from Swiss households. J. Environ. Econ. Manage.133, 103194 (2025). This article decomposes the causes of the solar rebound effect. Article Google Scholar Oliver, M. E., Moreno-Cruz, J. & Gillingham, K. T. Microeconomics of the solar rebound under net metering. J. Assoc. Environ. Resour. Econ.12, 1317–1353 (2025). This article explains why the rebound depends heavily on financial compensation and net metering design. Google Scholar Hofmann, F., Tries, C., Neumann, F., Zeyen, E. & Brown, T. H2 and CO2 network strategies for the European energy system. Nat. Energy10, 715–724 (2025). This article models infrastructure needs for a net-zero European energy system regarding a long-term transformation pathway, providing further context for flexibility requirements. Article Google Scholar White, L. V. & Sintov, N. D. Inaccurate consumer perceptions of monetary savings in a demand-side response programme predict programme acceptance. Nat. Energy3, 1101–1108 (2018). This study shows that consumer perceptions critically influence the success of demand-side measures, underscoring the need for smarter tariff design. Article Google Scholar Download references FernUniversität in Hagen, Hagen, Germany Mensur Delic & Michael Bucksteeg Institute of Energy Economics (EWI), University of Cologne, Cologne, Germany Michael Bucksteeg Search author on:PubMedGoogle Scholar Search author on:PubMedGoogle Scholar Correspondence to Mensur Delic. The authors declare no competing interests. Reprints and permissions Delic, M., Bucksteeg, M. Why Europe’s solar rollout must account for the solar rebound effect. Nat Energy (2026). https://doi.org/10.1038/s41560-026-02026-5 Download citation Published: Version of record: DOI: https://doi.org/10.1038/s41560-026-02026-5 Anyone you share the following link with will be able to read this content: Sorry, a shareable link is not currently available for this article.
Thank you for visiting nature.com. You are using a browser version with limited support for CSS. To obtain the best experience, we recommend you use a more up to date browser (or turn off compatibility mode in Internet Explorer). In the meantime, to ensure continued support, we are displaying the site without styles and JavaScript. Advertisement Nature Energy (2026)Cite this article The solar rebound effect (SRE) occurs when rooftop photovoltaic adoption increases household electricity consumption, driven by the perception of solar energy as a free resource. Although empirically observed, the SRE has not yet been accounted for in energy system modelling or abatement scenarios. This study integrates empirically derived SRE intensities into an open-source optimization model of the European energy system, translating behavioural effects into temporally distinct demand profiles. The results show that not only the magnitude but also the timing of the rebound determines its system impact. Additional demand leads to increases in renewable investment needs, flexibility requirements and overall system costs while inducing regressive effects, as households driving the rebound do not bear its full costs. The findings call for explicit inclusion of SRE in abatement scenarios and grid planning and highlight load-shifting incentives and energy efficiency policies as key tools to mitigate rebound effects and align demand with renewable generation. Imagine a single-family house with a rooftop photovoltaic (PV) system that, on sunny days, generates electricity perceived as free. This lowers the household’s effective electricity costs, leveraging the price elasticity of demand and incentivizing higher consumption, an outcome called the solar rebound effect (SRE)1. The SRE may also stem from income effects (as compensation through net metering or feed-in tariffs increases disposable income) and moral licensing, whereby households feel entitled to consume more after investing in green technology2,3. Although it is beneficial to individual households, this behaviour can undermine overall energy and emissions savings. Its potential scale becomes clearer when global energy forecasts are considered. According to the World Energy Outlook (Net Zero Emissions scenario), global electricity demand will reach 66,000 TWh in 2050, with more than 34,000 TWh supplied by solar power4. Following the 2050 supply trajectories of the Ten-Year Network Development Plan (TYNDP), approximately 30% of total solar electricity will be generated on rooftops5. Applying empirically observed SRE intensities from existing studies (7.7–33.0%, with an average of 17.2%), the resulting additional electricity demand in 2050 will range between around 800 and 3,400 TWh, equivalent to up to 5% of the global projected electricity demand. Although this figure might appear small in relative terms, the lower bound of this range corresponds to roughly one-third of the entire current electricity consumption of the 27 member states of the European Union in 2024 (2,729 TWh), and the higher bound is greater than this value6, underscoring the economic meaning of the SRE.Whereas the World Energy Outlook partially accounts for rebound effects in the transport sector, the SRE is ignored in the electricity and heat scenarios4. This applies equally to other global and European scenarios5,7,8. The scale of these potential effects underscores the need to examine their implications for regional energy systems. Especially given the rapid growth of rooftop PV across the European Union (EU)9, the SRE is particularly relevant due to its impact on electricity demand patterns. Although the behavioural dimensions of the SRE have been empirically studied (for example, refs. 10,11,12), its role within the energy system and in abatement scenarios remains unexplored (for example, refs. 13,14,15), leaving a notable research gap. Given these dynamics, the European power system provides a particularly suitable context for analysis, combining high PV adoption rates9 within the world’s most extensive interconnected power system16 and its ambitious climate targets14,17. To address this research gap, we integrate empirically derived SRE strengths into the open-source Stochastic European Energy Market Model (E2M2s)18,19,20,21,22,23. This analysis examines how varying temporal distributions of additional demand impact operations and investments within a sector-coupled framework. Unlike substitution-driven demand from electrification, the SRE reflects a behavioural response that adds consumption beyond service needs; our study, therefore, explicitly positions rebound-related demand within the broader context of sectoral and overall demand uncertainties. Specifically, we examine how the SRE influences technology deployment and system planning, total and CO2 abatement costs and consumer impacts through changes in electricity and CO2 prices. Existing studies distinguish between two main interpretations of the SRE24,25. The discrete solar rebound refers to the change in electricity consumption that occurs due to the adoption of PV systems, irrespective of the actual amount of electricity generated by these systems2,12,25,26,27,28. This interpretation treats the SRE as a relative increase in electricity consumption compared with the pre-adoption baseline. In contrast, the marginal solar rebound quantifies the additional electricity demand per unit of solar electricity generated in a specific time step after PV installation2,10,11,24,25,29,30,31,32. This is formally expressed as the ratio between the change in electricity consumption and solar PV generation before and after adoption33. The following analysis focuses on the marginal definition of the SRE, which guides model implementation. Figure 1 summarizes the marginal and discrete estimates reported in empirical studies published between 2015 and 2025. Shown are the reported SRE sizes by study, placed at the final year covered by the underlying data to convey how recent the evidence is relative to the publication date. The black circles and grey squares denote marginal and discrete estimates, respectively. The horizontal dashed lines indicate the simple means for each group (marginal = ~17.2%; discrete = ~14.1%). The lowest and highest reported values for marginal estimates are 7.7% (Aydın et al.29; the Netherlands) and 33.0% (Galvin et al.11; Germany). The lowest and highest reported values for estimates are 2.9% (Toroghi and Oliver26; USA) and 35.0% (Boccard and Gautier27 (Belgium) and Frondel et al.25 (Germany)). Studies reporting multiple estimates appear more than once. Only observational or data-driven studies using real-world evidence are included. Source data Most studies examine changes in consumption over several years and show persistent post-adoption increases in electricity use2,10,24,27. In particular, Beppler et al.24 and Havas et al.30 confirm long-term rebound effects over 6 months to 3 years after adoption. Aydın et al.29, Qiu et al.31 and Kim and Trevena28 likewise observe seasonal or regional fluctuations around a stable mean. Galvin et al.11 emphasize enduring behavioural drivers, such as perceived free energy, income effects and moral licensing. The decline found by Nguyen et al.12 probably reflects a methodological artefact in a setting with small-scale PV and without grid feed-in. Overall, the SRE can be regarded as a temporally persistent behavioural phenomenon in long-term modelling. Capturing the temporal resolution of the SRE is essential, yet most studies assess it only at an aggregate level, with fixed effect sizes. So far, only Kim and Trevena28, Qiu et al.31 and Aydın et al.29 provide a seasonal and temporal perspective, highlighting critical variations in the manifestation of SRE. Aydın et al.29 estimate an average intensity of 7.7%, with marked seasonal fluctuations ranging from 16% in summer to 3% in winter. Kim and Trevena28 identify an average SRE of 6.6%, with variations ranging from 4.9–8.3% across different climate zones, and a notable shift in additional demand towards evening and nighttime hours. The study by Qiu et al.31 comes to similar conclusions. A key challenge for assessing the SRE is the lack of high-resolution load profiles that capture sub-daily household usage before and after PV adoption. For this reason, we have opted for a scenario-based analysis that accounts for uncertainty in both the temporal distribution and the magnitude of the SRE, as shown in Table 1. The temporal distribution includes three profiles: (1) sweeping (the simplest interpretation); (2) simultaneous (rebound aligned with solar PV generation); and (3) dynamic (a time-resolved distribution of additional demand). In the sweeping profile, the effect relies on aggregated SRE estimates and is evenly distributed over time. Under this profile, the SRE is independent of direct solar power generation, representing a naive scenario. Yet, it allows the error to be assessed from an energy system modelling perspective with simplified mapping and no temporal resolution of the SRE. In the simultaneous profile, the SRE fully aligns with solar PV generation. This profile leads to a higher SRE during daytime and summer, as shown by Aydın et al.29. The dynamic profile represents the most realistic data-driven temporal distribution of the SRE. It combines predominantly simultaneous daytime rebound with an off-peak component to capture discrete elevated baseload and additional demand peaks during periods of low or no PV generation. The parameterization draws on hourly consumption patterns reported by Kim and Trevena28, which are used to calibrate the dynamics of the effect. Each rebound demand profile is examined with three empirical rebound intensities for residential households (rooftop PV owners only) to incorporate uncertainties in behavioural adaptation: 7.7% (low)29, 17.2% (average), derived from the reviewed studies, and 33.0% (high)11. The high scenario represents the upper empirical boundary of observed rebound magnitudes. Galvin et al.11 report an SRE of around 33% for German prosumers after 2011, driven by reduced feed-in tariffs and rising electricity prices that strengthened incentives for self-consumption. Comparable regulatory and market conditions still apply in most parts of Europe. More generally, post-adoption electricity demand may also reflect concurrent electrification trends that confound rebound attribution. Galvin et al.11 note this explicitly for heat pumps: electrified winter space heating is unlikely to be PV associated (given low winter PV output) and would therefore not be meaningfully attributable to solar rebound. Similarly, adopting an electric vehicle represents a substitution-driven increase in load and, by itself, does not constitute rebound. Accordingly, Galvin et al.’s 33% estimate reflects the behaviour-induced post-adoption increase in electricity use, which represents a rebound rather than a substitution-driven demand effect. A similarly high effect (28.5%) is found by Beppler et al.24 for US households. Together, these findings justify 33% as a realistic upper-bound scenario under strong economic incentives. All scenarios are applied to the European energy system (the current 27 member states of the European Union plus Norway, Switzerland, the UK and the Balkans) for 2030–2050. The European-wide impact of the SRE depends on both its magnitude and the timing of additional electricity use. In modelling terms, higher self-consumption reduces projected grid feed-in, which must be offset by additional generation to meet total demand. Even small rebound intensities can accumulate gradually, yet the timing of demand becomes system relevant only under higher PV penetration and stronger effect levels (Fig. 2). Although all three temporal profiles assume the same relative effect size, their total additional electricity demand (in TWh yr−1) differs slightly. This reflects the marginal definition of the SRE, where identical percentage effects translate into different absolute demand increases as solar capacity and temporal rebound patterns (midday versus evening) interact. a, Total electricity demand (including electrolysis) under the reference scenario and for the maximum SRE case. The annotations indicate the additional demand relative to the reference. b–d, SRE-induced additional electricity demand for low (7.7%;b), average (17.2%; c) and high (33%; d) effect strengths, shown for dynamic, simultaneous and sweeping profiles. In 2050, additional demand reaches 80.8 TWh (low), 160.7 TWh (average) and 314.9 TWh (high) for the dynamic profile; corresponding values are 63.1, 145.5 and 301.9 TWh for the simultaneous profile and 62.1, 140.8 and 276.3 TWh for the sweeping profile. Europe comprises the 27 member states of the European Union, plus the UK, Norway, Switzerland and the Balkans. Source data Accordingly, in 2050, the SRE will generate additional electricity demand of between 63 and 314 TWh yr−1, depending on the scenario. In relation to total electricity demand (including electrolysis) in Europe, this represents an additional increase of up to 5.1%. Although this may appear marginal at first glance, its relevance becomes evident in the context of sector-specific uncertainties. In the residential sector, electricity demand in 2019 amounted to 1,335 TWh yr−1, and long-term projections from existing studies, such as the TYNDP and EU reference scenarios, vary by around 300 TWh yr−1 (1,262–1,565 TWh yr−1), implying an uncertainty of roughly the same order as the SRE itself5,34. Similar variation exists in other sectors, such as transport (780–850 TWh yr−1) and industry (1,378–1,716 TWh yr−1). For total electricity demand including electrolysis, the expected range of 5,800–6,800 TWh yr−1 in these studies further illustrates the uncertainty shaping Europe’s future energy system. Against this backdrop, the additional SRE-induced demand of up to 314 TWh yr−1 constitutes a non-negligible source of uncertainty, particularly for residential electricity consumption and its contribution to system-level demand growth. To meet the additional demand, the energy system must rely on various flexibility options. These include battery storage for short-term balancing, hydrogen technologies for seasonal flexibility, and dispatchable generation to cover high residual load. Figure 3 illustrates the capacity expansion pathways up to 2050 for the average scenario (Extended Data Figs. 1 and 2 provide the results of other scenarios). PV capacity rises most under the dynamic and simultaneous profiles, since midday rebound demand can be met by solar generation. Moreover, both profiles efficiently utilize otherwise curtailed energy during peak generation hours. Higher intraday price spreads, particularly during the summer, enable higher revenues for battery storage, which leads to greater expansion of storage facilities. In the dynamic profile, this effect is further amplified by additional demand peaks during evening hours. At the same time, increased peak loads require additional backup capacity through hydrogen power stations to maintain generation adequacy in the event of a power outage. Under the sweeping profile, demand shifts to later hours, driving battery storage and wind capacity, as the rebound demand profile decouples, partly from solar generation. This highlights that the SRE’s temporal structure—not just its intensity—critically determines the needed technology mix. a, Installed capacity by energy source under the reference scenario (without SRE) and for the average SRE scenario, shown for the dynamic, simultaneous and sweeping temporal profiles (2030–2050). b, Difference in installed capacity relative to the reference, highlighting that the dynamic profile leads to the largest expansion of solar PV capacity, whereas the sweeping profile yields larger additions of wind power, battery storage and electrolysers due to the shifted timing of additional demand. The simultaneous profile enables efficient solar integration, but requires complementary hydrogen backup capacity to satisfy the peak adequacy constraint (equation (7)). Note that from 2045 onwards, the energy source described as conventional only includes nuclear power plants. Source data The generation mix in Fig. 4 reveals critical operational shifts beyond capacity expansion (Extended Data Figs. 3 and 4 present the results of other scenarios). Although the dynamic profile drives the highest solar PV generation (2,006 TWh in 2050), its key distinction lies in its use of flexibility: it stimulates a higher combined output from battery storage and hydrogen while causing the largest reduction in electrolyser operation compared with the reference (−37 TWh yr−1). This indicates that the additional storage facilities are effectively exploiting the wider intraday price spreads, driven by rebound demand and additional solar PV generation. The substantially higher generation from renewable energies is absorbed by the SRE and the changed flexibility mix, thereby reducing curtailment of renewables by up to 13.8%. As a result, hydrogen production in Europe becomes less attractive, offset by increased hydrogen imports. The simultaneous profile shows similar solar generation levels and system interactions. Still, it requires less flexibility because it eliminates rebound demand during off-peak periods. In contrast, the sweeping profile’s uniform demand maximizes absolute battery storage (304 TWh yr−1) and hydrogen output (526 TWh in 2050), highlighting its greater reliance on short- and long-term flexibility options. Moreover, electrolysis scales with the availability of renewable energy, particularly wind energy. a, Annual electricity production and electricity use for charging, pumping and conversion across the reference scenario (without SRE) and average SRE scenario (for the dynamic, simultaneous and sweeping profiles), shown for 2030–2050. Negative values indicate electricity use for electric vehicle charging, electrolysis, battery charging and pumped hydro pumping. b, Difference in electricity production relative to the reference scenario. Biomass and other renewable sources contribute marginally compared with the expansion in wind and solar power. Conventional electricity generation (including nuclear power, coal and gas) decreases sharply towards 2045 as the system approaches climate neutrality. c, Difference in electricity use for charging and pumping relative to the reference scenario. Only unidirectional charging is represented for electric vehicles. Source data Changes in the generation mix directly affect CO2 abatement costs. Total emissions follow a fixed path aligned with the Paris Agreement17, but the cost of avoiding them depends on how rebound demand is supplied. Because the SRE shifts demand volume and timing, it creates path dependencies and lock-in effects in capacity expansion, altering abatement costs. In the model, CO2 costs are calculated by multiplying the fuel-specific emission factors by the CO2 shadow price and dividing by plant efficiency, yielding technology- and time-specific CO2 cost coefficients applied to electricity and heat generation. These, alongside investment and operating costs, form part of the total system costs evaluated below. Given the model’s 2045 net zero target, efficient allocation of abatement becomes increasingly essential, especially regarding gas-based power, which fills gaps when storage falls short (Extended Data Fig. 5). In the dynamic and simultaneous profiles, extra demand aligns with midday PV output, keeping cost impacts low or even negative in 2040 (−€349 million for the high–simultaneous scenario). In 2035, the SRE raises the CO2 price, temporarily increasing CO2 costs. These elevated CO2 prices accelerate investment in renewable capacity, resulting in a cleaner generation mix and lower CO2 prices and abatement costs in 2040. Conversely, sweeping pushes demand into evenings and winters, maximizing gas use and costs (+€1.5 billion). Coal and lignite change little due to exogenous phase-outs. All monetary values are in constant 2023 euros. Overall, both the scale and timing of the SRE materially influence the cost of meeting climate targets. Over the long term, grid expansion is a key flexibility option. Using transmission shadow prices, we assess how the SRE alters the benefits of grid expansion in terms of potential system cost savings. Figure 5 compares the annual benefit of an additional megawatt of transfer capacity, computed as the sum of the hourly shadow prices of the transmission restrictions (equations (2) and (3)) relative to the reference, for 2040, a typical planning horizon. A value of 0.7, for example, corresponds to system cost savings of €0.7 million per megawatt and year. When considering the SRE, there is a marked change in the spatial pattern of grid expansion needs. Under the simultaneous and dynamic profiles, increased rebound demand coincides with solar generation and requires additional renewable deployment. Whereas Southern Europe can still expand PV capacity, most of the PV potential in Northwestern Europe is already exhausted by 2040, prompting further wind expansion in the UK. As a result, interconnection reinforcement between the UK and the Benelux region becomes economically viable. Under the sweeping profile, in contrast, rebound demand during off-peak periods is primarily met by additional wind generation and higher nuclear output in France, whereas hydropower reservoirs partly supply seasonal flexibility. Together, these developments create economic signals for stronger integration of Scandinavia, the North Sea region and France within the European grid. Overall, this finding suggests that omitting the SRE from current grid planning may yield divergent results in the cost–benefit assessment of individual interconnectors. a–c, Spatial distribution of changes in grid expansion benefits relative to the reference scenario without rebound (that is, the sum of the hourly shadow prices of the transmission constraints from equations (2) and (3) in million euros (m€) per megawatt per year), shown for the average scenario under the dynamic (a), simultaneous (b) and sweeping (c) rebound profiles.The line thickness encodes the congestion severity: thicker links indicate larger (more negative) shadow prices and thus greater potential system cost savings from additional cross-border transfer capacity. Near-zero values appear very thin. All monetary values are expressed in constant 2023 euros. Basemap administrative boundaries from the World Food Programme under an Open Government Licence v3.0. Source data From an economic perspective, the SRE leads to higher total system costs, especially as its intensity increases (Fig. 6). Cumulative additional costs rise from €12.7–18.6 billion under the low scenario to €72.3–82.9 billion under the high scenario by 2050. With low rebound intensity, only small differences between the profiles can be observed, with dynamic and sweeping patterns yielding nearly identical results (€18.6 billion versus €18.3 billion). This similarity results from two counteracting effects: under the dynamic profile rebound demand is higher as it extends into off-peak hours, whereas under the sweeping profile additional demand is lower, but the simplified mapping of the SRE introduces additional inefficiencies. As intensity increases, the role of temporal patterns becomes clear: the simultaneous profile is cheapest through optimized solar utilization, whereas the sweeping profile incurs the highest costs due to reliance on wind and costly flexibility options. The more realistic dynamic profile falls somewhere between the two. a, Total system costs (reference scenario and rebound cases) and the corresponding cumulative increase relative to the reference scenario. The cost impacts are small at low rebound levels, but become pronounced at higher intensities, reaching a maximum increase of 4.2% in 2050. b–d, Cumulative additional system costs relative to the reference scenario for the low (7.7%; b), average (17.2%; c) and high (33%; d) rebound effect strengths, shown for the dynamic, simultaneous and sweeping rebound profiles. System costs include investment, fixed and variable operating costs, start-up costs, curtailment, transport and hydrogen supply costs (as defined in the model objective function). All monetary values are expressed in constant 2023 euros. Source data Rebound demand increases CO2 prices under the decarbonization target by 204517 (Extended Data Fig. 5) and raises electricity market prices, as shown in Fig. 7 (see also Extended Data Figs. 6 and 7), with the effects shaped by national generation mixes and the timing of rebound demand. The dynamic profile produces moderate price increases (+€0.06 MWh−1 in France to +€0.76 MWh−1 in Belgium) due to its combined demand pattern, which requires additional flexibility, particularly in Central Europe, where gas-fired generation compensates for low solar periods. The simultaneous profile shows lower impacts or, in the case of high SRE intensity, even slightly falling prices in southern and south-eastern Europe, as it balances the increase in demand with solar peaks. Although total system costs rise due to additional investments in backup capacity, the short-term marginal costs of electricity production (that is, electricity prices) may fall in some cases—a positive side effect of the SRE. In contrast, the sweeping profile drives the largest price surges (+€1.55 MWh−1 in Germany and +€1.64 MWh−1 in Slovakia), as its uniform demand creates persistent reliance on gas-fired plants during winter, particularly in regions with limited flexibility and grid constraints. These patterns, consistent with earlier grid expansion analysis, highlight Central Europe’s particular vulnerability and underscore that rebound timing, not just its magnitude, determines both infrastructure needs and consumer prices. a, Load-weighted wholesale electricity price levels for the reference scenario without rebound (0% SRE). b–d, Price differences relative to the reference scenario for the dynamic (b), simultaneous (c) and sweeping (d) rebound profiles. Prices are defined as the load-weighted wholesale electricity price based on the hourly shadow price of the electricity demand-balance constraint in equation (1). Price impacts are spatially heterogeneous, with the largest increases concentrated in central Europe for the dynamic and sweeping profiles. All monetary values are expressed in constant 2023 euros. Basemap administrative boundaries from the World Food Programme under an Open Government Licence v3.0. Source data The SRE raises serious equity concerns due to its asymmetric cost distribution. Several interlinked factors contribute to its regressive impacts. First, the capital-intensive nature of PV systems, despite lower module prices, means that adoption remains rather correlated with higher income levels, a relationship further confined to households with a roof, creating an imbalance in access to the technology’s benefits. Second, Europe’s regulatory framework maintains tariff structures that tax grid electricity more heavily than self-consumed PV power35, effectively subsidizing rebound behaviour while passing the system costs on to all consumers. However, the current uniform cost distribution, rooted in an era of stable marginal generation costs, is increasingly challenged by variable renewables and rising capacity needs, making future cost allocation a policy choice rather than a historical convention. The temporal dimension of the SRE further complicates this picture. When households shift increased electricity consumption to periods with low solar generation, the system must deploy expensive backup capacity to meet this demand. These costs manifest as higher wholesale electricity prices that affect all consumers equally (Extended Data Fig. 8). As with CO2 costs, the burden of maintaining this capacity is borne by all consumers, creating an implicit cross-subsidy from non-adopters to adopters that widens energy inequalities, especially for lower-income households who spend a larger share of income on energy and lack self-generation36,37,38,39. This study provides a comprehensive model-based analysis of the SRE and its system interactions, using Europe as an example. Previous research has focused on empirical description and largely overlooked its technological and economic implications. Our findings reveal that the SRE cannot be analysed in isolation; it is embedded in complex interactions with other energy system elements. Overall, the SRE entails both adverse and beneficial effects that differ across spatial and temporal dimensions. The increased electricity demand requires additional renewable investments to achieve climate neutrality, while also creating challenges for integrating renewables and necessitating greater reliance on flexibility options. This raises total system and end-consumer costs. However, potential positive effects arise from the specific temporal distribution of additional consumption: under the simultaneous profile, the SRE may reduce renewables curtailment, binding grid constraints and expansion needs. Moreover, the SRE can also reflect welfare gains, as prosumers benefit from low-cost self-consumption, enhancing comfort or energy services. The results should be interpreted in light of the model’s limitations. Private households are aggregated to capture the system-level focus. One potential enhancement is a better differentiation of PV and storage types. The model also overlooks price elasticity, potentially overstating the SRE’s regressive effects, yet low-income, price-sensitive households remain disadvantaged. Additionally, high-resolution, hourly data on household demand and generation would improve the model’s accuracy. Future model-based research should extend our approach to include interactions with additional rebound effects across coupled sectors. Moreover, the SRE’s magnitude may not be static but endogenous to technology co-adoption. Empirical studies indicate that battery storage can mitigate rebound behaviour by shifting consumption patterns, whereas electric vehicles and heat pumps may amplify it2. Capturing such interactions would improve forecasts of future rebound trajectories and better reflect the dynamic nature of household energy systems. The results of this study provide a foundation for developing policy strategies that enhance the positive effects of the SRE while mitigating its negative impacts. The first practical takeaway is that the SRE should be explicitly integrated into abatement scenarios and simulation studies, because our findings show that excluding it leads to different system outcomes. Building on this insight, supporting households in shifting flexible demand to solar-rich hours (through demand-side response instruments such as time-varying tariffs) can amplify the system benefits observed for the simultaneous profile36. Our findings call for greater attention to load-shifting policies that promote closer alignment between consumption and renewable generation37. Making solar PV subsidies conditional on energy efficiency measures can also be a relevant tool for reducing the SRE, as energy-efficient households tend to exhibit lower rebound effects38. At the European level, these findings underscore the importance of integrated policy frameworks that address both behavioural incentives and infrastructure gaps. Finally, this study suggests that omitting the SRE from current grid planning may yield divergent results in the cost–benefit assessment of individual interconnectors, underscoring the importance of EU-wide coordination on grid expansion. The modelling of the SRE captures a broad range of systemic interactions, from initial investment decisions in PV systems to dynamics in the wholesale electricity market. A central challenge lies in the temporal alignment between solar power generation and the additional demand it triggers, as this coincidence critically shapes system-level impacts. The following text outlines how relevant behavioural assumptions can be incorporated into energy system modelling, with particular attention to the structural decisions and temporal patterns required to accurately represent the SRE. The occurrence of the SRE involves a series of decisions, from planning and investment to long-term use of the solar PV system, as detailed in Extended Data Fig. 9 and the description below. Information and planning form the initial phase, during which the person collects detailed information about PV systems, compares offers and examines various options. In this period, essential considerations are made, ranging from financial conditions (for example, credit financing or leasing) to technical details39. This also includes assumptions about the anticipated electricity consumption, usually based on the most recent electricity bill. This is followed by the investment phase, in which the person decides to install a solar PV system. At this stage, risk and time preferences may play an important role, for example, due to uncertainties about investment costs and the future economic benefits of the investment40,41,42. After ordering, there is usually a time lag before the installation is completed. Once the PV system has been installed, the first-use phase begins, during which the electricity produced is consumed for the first time. Subsequent adaptation and optimization reflect that the widespread availability of inexpensive renewable electricity, produced at nearly zero marginal cost, is driving a change in consumption patterns by making electricity more accessible10. In this phase, households optimize their electricity consumption behaviour to maximize their consumption or utilization of the energy generated. This is done, for example, by shifting the use of electrical devices to the hours of high PV generation29. The following rebound phase shows that awareness of the cheaper or perceived free solar power leads to increased electricity consumption. As the study by Beppler et al.24 shows, prosumers generally only adjust their consumption when they recognize the reduced electricity costs from the PV system. Moreover, households can be expected to increase their use of energy-intensive appliances with the installation of PV systems43. Examples are the longer operation of air conditioning systems or the selection of more energy-intensive programmes for dishwashers and washing machines. Finally, interaction effects cover the exchange between rebound demand and wholesale market dynamics. The higher-level system perspective is considered, particularly regarding the impact of the rebound effect. Surplus solar power fed into the grid in the past is no longer available to other households due to prosumers’ private consumption. This can limit the availability of cheap electricity for other consumers and can have a lasting impact on the electricity markets and capacity planning44. The first assumption for SRE modelling is derived from the outlined decision-making process. A household first decides to invest in a solar PV system, installs it and subsequently begins using the generated electricity. The rebound effect only arises during the usage phase. Crucially, the investment decision is based on current conditions—particularly existing electricity consumption—at a time when rebound effects have not yet manifested and therefore do not influence the initial choice. Note that the anticipation of additional electricity consumption (as would occur due to the purchase of an electric car, for example) is not a rebound effect but a substitution effect45. The time lag between the investment decision and the occurrence of the SRE necessitates a dynamic–recursive model structure to capture the time sequence correctly. Furthermore, it is assumed that actors base their decisions on myopic expectations. This means that current conditions are extrapolated into the future and the SRE is thus not anticipated. Another essential modelling requirement is the representation of electricity consumption during the usage phase of the solar PV system. Energy system models generally consider an hourly resolution, which poses challenges for integrating aggregated annual SRE values derived from empirical studies. As outlined in the empirical foundation, the absence of high-resolution load data prevents the rebound structure from being modelled accurately at an hourly level. Due to this data gap, we opted for a scenario-based approach, which addresses the simultaneity or non-simultaneity of PV generation and the SRE at a conceptual level. This is particularly relevant because the temporal distribution of the rebound remains empirically unresolved (that is, the additional consumption may occur at different times of day). Extended Data Fig. 10 illustrates this by juxtaposing a scaled PV generation profile based on ENTSO-E Transparency Platform data for actual generation per production type (solar)46 on the left with a representative load profile for a prosumer household with a PV system based on the BDEW P25-profile47 on the right. Under the simultaneous profile, according to microeconomic theory, a fall in the price of electricity, especially down to a price of zero, leads to an increase in demand. This is due to the price elasticity of demand, which measures how much the quantity demanded responds to price changes, following the law of demand48. In private households with a PV system, the perception of free solar power creates an incentive to increase the use of electrical devices, both in frequency and duration. Accordingly, the SRE should be temporarily linked to solar power generation. This hypothesis is supported by the results of Aydın et al.29, which show that electricity consumption increases markedly during periods of high PV generation. From this, the simultaneous profile can be derived (see also equation (4)). The green curves in Extended Data Fig. 10 proportionally follow the solar feed-in represented by the orange reference curve. In the model, this behaviour is implemented using a proportional factor based on PV generation and the strength of the considered SRE. In the sweeping profile, the additional electricity demand from the SRE is evenly distributed over time. This pattern is based on the findings of Kim and Trevena28, who observed increased electricity consumption even outside solar power generation times. In contrast with the simultaneous profile, the blue dotted line in Extended Data Fig. 10 shows a smoothed, constant distribution of additional consumption to represent the shift into the off-peak periods. It symbolizes a uniform increase in consumption throughout the day, without marked peaks (see also equation (5)). The sweeping and simultaneous profiles can be considered extreme scenarios that make specific assumptions about consumption behaviour. Both approaches can lead to overestimates: the simultaneous profile ignores potential shifts into the evening hours, whereas the sweeping profile underestimates actual consumption during solar production. A third profile addresses these weaknesses and offers a more pragmatic, data-driven approach to SRE allocation. In Extended Data Fig. 10, the dynamic profile is represented by the slightly spread purple curve, which combines simultaneous rebound during daytime hours with a discrete off-peak demand component, reflecting both immediate consumption during PV generation and elevated baseline demand during periods of low or no solar output (see also equation (6)). This approach is calibrated using empirically observed consumption patterns reported by Kim and Trevena28, ensuring the profile captures the full temporal complexity of rebound behaviour. The open-source E2M2s model is a long-term planning and dispatch model for the European power, heating and mobility sectors18. It is formulated as a linear problem and based on a dynamic, recursive optimization approach that simulates selected years (2030–2050, in five-yearly stages) under myopic expectations. The model endogenously expands generation and storage capacity within 34 European market areas (countries). At the same time, cross-border electricity trade is represented by a net transfer capacity-based approach (paired with an exogenously given grid expansion path). The objective is to minimize total system costs, including investment and fixed and operating costs, thereby replicating a competitive market outcome. To reduce computational complexity, the modelling period is divided into eight representative days, each with seven time segments, capturing different weekdays, months and load patterns. A set of recombining trees is applied to reflect the volatility of renewable generation. Beyond power and heat, the open-source model also covers aspects of the mobility and hydrogen sectors. Numerous applications of E2M2s are reported by Swider and Weber19, Spiecker et al.20, Spiecker and Weber21, Bucksteeg et al.22 and Blumberg et al.23. The following describes the relevant equations and adjustments to the model. The demand balance equation ensures that total electricity generation meets the electric load in each region at every time step. In simplified form, it states that the sum of the terms of the regional load ({l}_{r,t}), summarized electricity consumption of storage and electrolyser ({P}_{r,u,t,n}^{mathrm{cons}}) and solar PV-induced rebound ({mathrm{SRE}}_{r,u,t}) must equal the summarized power production ({P}_{r,u,t,n}) and net exports ({E}_{{r}^{{prime} }to r,t,n}-{E}_{rto {r}^{{prime} },t,n}). Parameters are denoted by lowercase letters, while decision variables appear in uppercase (see also the nomenclature in the Supplementary Information). The demand balance plays a central role in understanding the impact of the SRE on electricity supply and the utilization of flexibilities, such as storage and electrolysis. This is because increased solar energy production stimulates electricity consumption via the SRE, influencing power plant dispatch and the use of flexibility options, thereby altering electricity market dynamics. These effects also extend to cross-border electricity exchange and the associated grid infrastructure. Although meeting demand is essential, the power system must also operate within the physical constraints of its infrastructure. This limitation is mathematically expressed by ensuring that the power flow ({E}_{rto {r}^{{prime} },t,n}) from region (rto r{prime}) to region ({r}^{{prime} }to r) at a given node and time segment does not exceed the available cross-border capacities for ({C}_{f}(rto {r}^{{prime} })) and ({C}_{f}({r}^{{prime} }to r)). Analysing the shadow prices associated with this restriction allows us to assess the impact of the additional electricity demand due to the SRE on the benefits of network upgrades. In the context of the demand balance equation presented above, the simultaneous solar rebound ({mathrm{SRE}}_{r,t,n}^{mathrm{sim}}) is modelled so that the additional electricity consumption increases proportionately to the produced solar energy. To this end, a rebound term is included in the balance equation in addition to the basic load, which is based on the capacity of the previous year cr,u, the capacity factor (that is, the generation profile) ({phi }_{r,u,t,n}), a selected effect size sre and the household share α. This formulation uses the marginal SRE definition, in which additional consumption is expressed per unit of solar generation. This allows for consistent integration of the rebound effect into the temporal generation structure, directly linking additional demand to the hourly PV output profile. For the sweeping profile, the rebound is evenly distributed throughout the day, depending on the selected intensity. This is modelled by a time-averaged PV profile based on the capacity factor ({phi }_{r,u,t,n}). As a result, the SRE occurs not only during PV production times but also during off-peak periods, as it is spread evenly over time. The dynamic solar rebound ({mathrm{SRE}}_{r,t,n}^{mathrm{dyn}}) is a combination of a PV-coincident marginal component and an off-peak discrete baseline uplift. Based on the simultaneous profile, the first term links additional consumption proportionally to contemporaneous PV generation, whereas the second captures consumption increases that also occur when PV output is low or zero. The time-varying weights ({beta }_{r,t}^{mathrm{sim}}) and ({beta }_{r,t}^{mathrm{off}}) govern the share of both components, enabling both profiles to overlap, especially at the beginning and end of the day. where and Furthermore, the model includes a capacity constraint to ensure sufficient generation resources are available to cover peak demand, as the representative-day approach might not perfectly capture actual annual load peaks. The maximum total electricity demand by country is given on the right-hand side of this constraint, whereas the left-hand side aggregates all secure capacity. This includes conventional units and storage (weighted by an availability factor), minimum guaranteed hydro inflows and the lowest feasible production from variable renewables in a worst-case scenario (for example, a dark doldrum (dunkelflaute) situation). Here, availt,u and ({phi }_{t,r,u}) capture technology- and region-specific availability factors, ({c}_{r,u}) denotes installed capacities, ({w}_{t,r,u}) represents the minimal usable water inflows and ({L}_{r}^{max }) is the maximum total electricity demand. Depending on the SRE case, the maximum total electricity demand varies. Part of the electricity demand is endogenous, caused by the electricity consumption of electric cars, electrolysers and heat pumps. The following formula defines the peak electricity demand and illustrates, through the rebound term, how higher electricity demand can arise as PV generation on private house roofs increases. Accordingly, the maximum electricity demand ({L}_{r}^{max }) is given by the maximum of the summarized exogenous electricity demand ({l}_{r,t}), additional demand from electromobility ({L}_{r,t,n}^{mathrm{emob}}) (only charging electricity), electricity demand from electrolysis ({L}_{r,t,n}^{{{rm{H}}}_{2}}), the heat pump demand ({L}_{r,t,n}^{mathrm{heatpump}}) and the solar rebound term ({mathrm{SRE}}_{r,t,n}) (sweeping, simultaneous or dynamic). The modelling framework integrates diverse data sources to provide a comprehensive representation of the European energy system. Key inputs include renewable energy availability, demand forecasts, the existing power plant fleet (utilizing a brownfield approach) and techno-economic parameters such as investment costs and fuel prices. These parameters are primarily sourced from established references, including the TYNDP5 and World Energy Outlook4. Electricity, hydrogen, mobility and district heating demands are exogenously modelled based on the Distributed Energy scenario of the 2024 TYNDP5. Based on bottom-up national input data, this scenario accounts for reduced energy demand through behavioural and technological shifts. These include higher renovation rates, lower surface per person and higher levels of energy-efficient consumer behaviour. At the same time, the scenario also highlights how new consumption patterns can partially counteract such efficiency gains; for instance, through the use of reversible heat pumps for cooling in summer, which may increase electricity demand despite their heating efficiency. The scenario data include the uptake of new electricity consumers (electric vehicles, heat pumps and air conditioning systems). Electricity demand (excluding electrolysis) in Europe exhibits a substantial upward trend, increasing from approximately 4,000 TWh in 2030 to over 5,000 TWh by 2050, driven by higher electrification. Hydrogen demand is projected to grow substantially, from 524 TWh in 2030 to 1,400 TWh by 2050. In comparison, district heating demand growth remains relatively modest over the same period, reflecting its stable role within the energy system. In contrast, the SRE is not captured within the TYNDP demand pathways. Our framework introduces the SRE as an endogenous electricity demand that depends on solar PV adoption and generation. Furthermore, an aggregated SRE is considered, meaning that empirically identified positive and negative rebounds are implicitly included29. The model includes Europe’s interconnector infrastructure for electricity and planned hydrogen networks. Net transfer capacities for electricity and hydrogen transfer capacities enable energy exchange between regions, which is essential for balancing supply and demand under high renewable energy penetration. Both net transfer capacities and hydrogen transfer capacities are treated as exogenous parameters that follow predefined expansion trajectories rather than being endogenously optimized within the model. The data for infrastructure development are based on the 2024 TYNDP5 and the European Hydrogen Backbone49,50. The decarbonization pathway is represented through a CO2 cap that limits emissions across the electricity and heat sectors. This constraint enforces a gradual reduction in allowable emissions, starting in 2030 and reaching CO2 neutrality by 2045, following a trajectory based on the European climate objectives17. The CO2 price, determined endogenously through the dual variable of the constraint, reflects the marginal cost of emission reductions. Investment costs and technology lifetimes for capacity expansion are sourced from the Net Zero Emissions by 2050 scenario in the World Energy Outlook 20244, ensuring alignment with internationally recognized decarbonization pathways. The model distinguishes between residential (rooftop) PV and utility-scale PV. The SRE is exclusively linked to the residential rooftop segment1, parameterized by ({alpha }_{r,t}), which specifies the share of total PV capacity installed at the household level. Respective solar generation shares are primarily derived from TYNDP projections5. All input, processed and output data used in this study are available for access or reproduction via the GitHub repository branch at https://github.com/ude-ewl/osE2M2s/tree/Paper-SRE. Scenario-specific output and processed results are available there. All figures were created using Python, specifically the package Matplotlib. 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Article Google Scholar A European Hydrogen Infrastructure Vision Covering 28 Countries (European Hydrogen Backbone, 2022); https://ehb.eu/files/downloads/ehb-report-220428-17h00-interactive-1.pdf Hydrogen Infrastructure Map (ENTSOG et al., 2022); https://www.h2inframap.eu/ Download references We thank all of the colleagues who shared their insights and suggestions for this study at various conferences and workshops. Special thanks go to S. Poier, O. Ruhnau and J. Thomsen for valuable feedback throughout the development of this work. We also thank J. Radek and M. Breder for help with preparing the dataset used in this study. Open access funding was enabled and organized by Projekt DEAL. Open access funding provided by FernUniversität in Hagen. FernUniversität in Hagen, Hagen, Germany Mensur Delic & Michael Bucksteeg Institute of Energy Economics, University of Cologne, Cologne, Germany Michael Bucksteeg Search author on:PubMedGoogle Scholar Search author on:PubMedGoogle Scholar M.D. and M.B. were responsible for software development, validation, formal analysis, investigation and writing (original draft and reviewing and editing). M.D. was responsible for data curation and visualization. M.B. was responsible for conceptualization, methodology and supervision. Correspondence to Mensur Delic. The authors declare no competing interests. Nature Energy thanks Dogan Keles and the other, anonymous, reviewer(s) for their contribution to the peer review of this work. Publisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations. a, Installed capacity (GW) by energy source in the reference scenario (without SRE) and in the low SRE scenario, shown for the dynamic, simultaneous and sweeping rebound profiles (2030–2050). b, Difference in installed capacity relative to the reference (GW). From 2045 onwards, Conventional only includes nuclear power plants. Source data a, Installed capacity (GW) by energy source in the reference scenario (without SRE) and in the high SRE scenario, shown for the dynamic, simultaneous and sweeping rebound profiles (2030–2050). b, Difference in installed capacity relative to the reference (GW). From 2045 onwards, Conventional only includes nuclear power plants. Source data a, Annual electricity production and electricity use for charging/pumping and conversion across the reference scenario (without SRE) and the low SRE scenario (dynamic, simultaneous and sweeping profiles), shown for 2030–2050 (TWh/yr). Negative values indicate electricity use for electric-vehicle charging, electrolysis, battery charging and pumped-hydro pumping. b, Difference in electricity production relative to the reference scenario (TWh/yr). c, Difference in electricity use for charging/pumping relative to the reference scenario (TWh/yr). Only unidirectional charging is represented for electric vehicles. Source data a, Annual electricity production and electricity use for charging/pumping and conversion across the reference scenario (without SRE) and the high SRE scenario (dynamic, simultaneous and sweeping profiles), shown for 2030–2050 (TWh/yr). Negative values indicate electricity use for electric-vehicle charging, electrolysis, battery charging and pumped-hydro pumping. b, Difference in electricity production relative to the reference scenario (TWh/yr). c, Difference in electricity use for charging/pumping relative to the reference scenario (TWh/yr). Only unidirectional charging is represented for electric vehicles. Source data a, Low scenario (7.7% SRE): CO2 prices (green labels, €/t) and the associated abatement cost components (stacked bars; see legend) across model years for the dynamic, simultaneous and sweeping demand profiles. b, Average scenario (17.2% SRE; same as in a). c, High scenario (33% SRE; same as in a). Abatement costs represent CO2-related cost components implied by the CO2 shadow price. All monetary values are expressed in constant 2023 euros. Source data a, Reference scenario without rebound (0% SRE): load-weighted wholesale electricity price level (€/MWh). b, Price differences relative to the reference scenario (€/MWh) for the dynamic rebound profile. c, Same as in b, but for the simultaneous profile. d, Same as in b, but for the sweeping profile. Prices for households are defined as load-weighted wholesale electricity prices based on the hourly shadow price of the electricity demand-balance constraint in Eq. 1. Price impacts are spatially heterogeneous. All monetary values are expressed in constant 2023 euros. Basemap administrative boundaries from the World Food Programme under an Open Government Licence v3.0. Source data a, Reference scenario without rebound (0% SRE): load-weighted wholesale electricity price level (€/MWh). b, Price differences relative to the reference scenario (€/MWh) for the dynamic rebound profile. c, Same as in b, but for the simultaneous profile. d, Same as in b, but for the sweeping profile. Prices for households are defined as the load-weighted wholesale electricity price based on the hourly shadow price of the electricity demand-balance constraint in Eq. 1. Price impacts are spatially heterogeneous. All monetary values are expressed in constant 2023 euros. Basemap administrative boundaries from the World Food Programme under an Open Government Licence v3.0. Source data Each box-and-whisker plot summarizes the distribution of annual average wholesale electricity prices across market zones for a single scenario (n = 34 market zones; one value per zone). The thick horizontal line is the median; the multiplication symbol marks the arithmetic mean; the box encloses the interquartile range (25th–75th percentile); and whiskers extend to the most extreme values within 1.5 times the interquartile range. The reference scenario (0% SRE) serves as the control case. The boxplots illustrate how SRE-induced demand shifts affect the distribution of procurement-relevant wholesale prices across zones in 2040. Source data a, Information and planning involve collecting details, comparing offers, and considering finances and technical aspects. b, The investment decision reflects deciding to adopt PV under risk preferences. c, Installation covers the commissioning of the PV system, typically with a time lag. d, At first use, the household becomes a prosumer and starts self-consuming PV electricity. e, Adaptation and optimization describe adjusting consumption patterns to maximize PV electricity use. f, In the rebound phase, electricity use increases as solar power is perceived as ‘free’. g, Interaction effects capture system-level impacts on markets and other consumers. a, Normalized PV generation profile and the corresponding incremental rebound demand under the sweeping, simultaneous and dynamic profiles. b, Synthesized household load profile (without rebound) and the resulting total load when adding the profile-specific incremental rebound demand. Dashed lines indicate incremental demand attributable to the SRE. Source data Nomenclature (definitions of indices, sets, parameters, variables and equations). E2M2s SRE source code and accompanying input files for reproducing the optimization runs, including a README mirror of the GitHub repository at https://github.com/ude-ewl/osE2M2s/tree/Paper-SRE. Empirical data. Processed model output data as plotted. Processed model output data as plotted. Processed model output data as plotted. Processed model output data as plotted. Processed model output data as plotted. Processed model output data as plotted. Processed model output data as plotted. Processed model output data as plotted. Processed model output data as plotted. Processed model output data as plotted. Processed model output data as plotted. Processed model output data as plotted. Processed model output data as plotted. Processed model output data as plotted. Generation profiles for panel a and standard load profile for panel b. Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. Reprints and permissions Delic, M., Bucksteeg, M. Implications of the solar rebound effect for the European energy transition. Nat Energy (2026). https://doi.org/10.1038/s41560-026-02031-8 Download citation Received: Accepted: Published: Version of record: DOI: https://doi.org/10.1038/s41560-026-02031-8 Anyone you share the following link with will be able to read this content: Sorry, a shareable link is not currently available for this article.
FORT FRANCES — The Independent Electricity System Operator (IESO) has announced contracts with proponents to build 14 solar- and wind-power generating stations across Ontario, three of which are in the Rainy River District. The three solar projects are proposed to be built in Fort Frances, Chapple, and unincorporated Rainy River territory, generating a total of 284.40 megawatts. There are also two wind projects in the Northwest that will generate a collective 400 MW, located in Nipigon and the unorganized Thunder Bay area. “The energy task force has identified, for a number of years, that we are short in terms of the energy we have on a regular basis in the region, so this is really, really good news” said co-chair of NOMA’s Northwest Energy Task Force, Iain Angus. Fort Frances Mayor Andrew Hallikas said that the projects are huge for the town, which he hopes will eventually be known as a green energy centre. The construction of the Fort Frances solar farm will create about 120 jobs for the community, and its 57.2 MW output will power 8,000 homes in the province, according to Hallikas. Fort Frances already has a hydro-electric dam, and in the next year expects construction to commence on a bio-refinery that refine waste fibre from the forest into de-carbonized fuel. Hallikas said that the Fort Frances Power Corp. will need higher voltage power lines and upgraded transformers in the transformer station in light of the upcoming power generation. The town is also in the process of creating a micro-grid that will allow them to be self-sustaining in energy. Combined with the 60.00 MW coming from the project in Chapples near Barwick and the 167.20 megawatts from the Rainy River unorganized project, the three solar farms will create considerable amounts of energy that will be especially useful to the mines in Northwest. “Right now, in terms of hydro-electric, we’re putting out in the range of 600 to 700 megawatts of power on a continuous basis. But we’ve had droughts […] that reduces it down to about 230 MW as all we can guarantee, so we need other forms of ongoing power,” Angus said. Angus confirmed that, as of now, there are no approved battery storage plant projects, although Mayor Hallikas suggests that a battery storage group in conjunction with the new solar farm would further help the town in becoming energy independent. While the cities do not have ownership stakes in the projects, Hallikas points out that every project is at least 50 per cent First Nation owned. “The province of Ontario has made a conscious decision that any project that has First Nation partnership will get an advantage over those that are strictly non-Indigenous,” said Angus. “[This] enables them to be a real partner in the projects, and that creates employment for First Nations residents as well as a revenue stream for the communities themselves.” Angus called it a win-win situation for all.
A new report from Metal Focus reveals that global silver market remains structurally tight, with elevated prices, a fifth consecutive annual supply deficit in 2025, and ongoing mine and recycling constraints despite modest production growth. At the same time, PV-driven silver demand is falling sharply due to cost pressure and thrifting. Image: Heraeus From pv magazine Global The global silver market remains structurally tight despite weakening demand from the photovoltaic sector, with elevated prices and constrained supply continuing to shape the PV manufacturing landscape. According to the latest World Silver Survey 2026 by independent research consultancy Metals Focus, silver prices rose sharply through 2025, averaging just over $40 per ounce, a 42% year-on-year increase, before climbing to even higher levels in early 2026. The rally was driven by a combination of strong investment demand, tightening physical supply, and ongoing geopolitical and macroeconomic uncertainty. At the same time, the solar sector, long a key driver of industrial silver demand, is entering a period of adjustment. Silver demand from PV producers declined by 6% in 2025 to 186.6 million ounces and is now forecast to fall by a further 19% in 2026 to around 151 million ounces. “Industrial offtake slipped by 3% to 657.4 million ounces, marking the first post-pandemic decline, as a contraction in PV demand and thrifting elsewhere outweighed gains linked to AI-related data-centers, high-speed transmission hardware, EV penetration and charging infrastructure,” the report reads. The decline in PV-related silver consumption reflects a combination of technological change and cost pressure. As silver prices increased, module manufacturers accelerated efforts to reduce silver loadings per cell by adopting thrifting strategies and alternative metallization approaches. The analysts explained that intense competition and rising raw material costs have pushed producers to cut silver usage, even as global solar installations continue to grow, noting that this growing decoupling between PV capacity expansion and silver demand marks a significant shift for the industry. On the supply side, global silver mine production rose significantly last year, supported by mining project ramp-ups in Latin America. Recycling also increased modestly, reaching a 13-year high of 197.6 million ounces. Despite these positive results, the silver sector recorded its fifth consecutive annual deficit in 2025, totaling 40.3 million ounces, with another shortfall expected in 2026. Structural constraints, including declining ore grades, operational disruptions, and a limited pipeline of new projects, are expected to continue limiting supply growth. Recycling volumes are rising but remain constrained by refinery bottlenecks and capacity challenges. The report also reveals that, while PV demand weakened, other segments such as AI-driven data centers, electric vehicles, and power infrastructure continued to support consumption. Looking ahead, total industrial demand is expected to decline again in 2026, with further weakness in PV outweighing gains in emerging applications. Silver, however, is expected to remain a strategic material risk for PV manufacturers, even as technological innovation continues to reduce dependence on the metal. According to recent analysis by the Silver Institute, the photovoltaic industry is expected to use less silver in 2026. Silver paste currenly accounts for around 10-20% of total solar cell costs, creating a difficult environment for manufacturers already facing overcapacity, falling module prices and squeezed margins. 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. More articles from Emiliano Bellini Please be mindful of our community standards. Your email address will not be published.Required fields are marked *
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Tigo Energy has expanded the availability of its Inverter Power Output Control (IPOC) to the 3.8-kW Tigo EI Inverter designed for smaller residential systems with utility interconnection constraints. IPOC provides installers with the ability to limit the AC power output of Tigo inverters via software during the commissioning process. The ability to reduce the maximum AC…
Analysis of longitudinal survey data has explored the link between intended and actual solar panel adoption in UK households. It finds that while most households that had intention of installing solar in 2012-13 were yet to do so by 2021-22, serious intention to install solar still increases the likelihood of adoption more than other factors such as income and environmental perceptions. Image: Lara John/Unsplash Intention to install household solar in the U.K. has not often translated to actual adoption, new research suggests. The research paper “Do intentions matter in household solar panel adoption? New evidence,” available in the journal Energy Economics, analyzes the link between stated intentions and actual adoption of UK household solar installations by using data from the UK Household Longitudinal Study. The survey is considered one of the world’s largest panel surveys, with a sample size of 40,000 households and approximately 100,000 individuals. The research team, from Sydney’s Macquarie University, Charles Darwin University, and Queen Mary University of London, used survey data from 2012-13, 2018-2019 and 2021-22, analyzing data on intention to install household solar and actual solar adoption against factors including age, income, material wealth, whether someone rents their property and environmental perceptions. Rohan Best, from Macquarie University and corresponding author of the report, told pv magazine that a key finding of the research was that while intentions do matter for household solar adoption, the link between intentions and actual adoption remains nuanced. Figures available in the paper state that nearly 90% of households who had said they were seriously considering adopting solar panels in the 2012-13 survey had not yet installed solar by the 2021-22 survey. Despite this finding, the paper says that solar intentions, proxied by serious consideration, still exerts a robust positive effect on actual adoption, increasing the likelihood by three to seven percentage points. For comparison, variables such as income contributed zero to two percentage points on the likelihood of adoption. Additional analysis found households that had rejected the idea of installing solar panels after consideration in 2012-13 were more likely to have adopted solar by 2021-22 compared to those who stated they had not thought about adopting solar. “Having considered but rejected solar panels appears to make subsequent adoption more likely compared to those who had not given consideration to solar panels earlier,” Best said. The researchers also found the link to environmental perceptions is stronger towards solar intentions than solar adoption. Elsewhere, income was found to have a minor influence on solar adaption, with income’s influence mostly explained by related factors such as wealth and renting. Best told pv magazine this finding points towards the need to broaden policy considerations around solar adoption beyond income, before suggesting that a separate solar adoption scheme could be implemented for renters. “Renters make up a substantial fraction of households in every country, so policies specifically targeting renters could have potential everywhere,” he added. Best also said the research findings highlight that there would be value in governments eliciting information on household willingness and ability to pay for solar panels, through mechanisms such as an equitable reverse auctions trial. “Reverse auctions have been used in other related contexts like utility-scale energy to pursue cost-effectiveness such that the lowest cost bid is successful,” Best explained. “In a household context, fairness can be pursued with sub-auctions for sub-groups of households based on economic characteristics of a household like their wealth or income to ensure that households could compete with others in a similar economic position.” Best also told pv magazine he believes the research findings can be applied to influence policy design in national markets other than the UK, as a lack of information on household willingness or ability to pay for solar is ubiquitous across national governments. “If one government can take novel actions to make improvements for some of these challenges, then other governments can benefit by following successful trials,” he continued. “If governments lack information at the household level, then subsidy schemes would naturally continue to be provide more than is necessary for some households but less than required for others. Instead, better targeting of subsidies can help more people for a given cost to the government.” Best added that the results are also relevant to markets linked to solar adoption, such as the uptake of home battery systems. “This is because of the widespread issues for any technology investment including upfront cost constraints, split incentives for renters/landlords, and information shortfalls for governments considering subsidy schemes,” he said. 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. More articles from Patrick Jowett Intentions mean nothing when installers mark materials up 100-150% so that repayment term stays just under 20 years. When it should be 6-10 years. MCS scheme that was supposed to protect consumers is actually hurting them. Actually requirement for MCA certified installation in order to get export tariff is. Without MCS certified money grabbing installers i coud DIY install the same hardware at 30-40% of the cost, get it electrically connected and tested by sparky and be done with it. Huge part of MCS is ensuring solar is not missile to people who won’t benefit from it and making sure there is insurance for 25 years of repayment term. Electrical safety is 25% if not less of MCS related costs, so why should DIY installations be penalised for not lining pockets MSC certified installers? Every NicEic qualified electrician can connect rooftop solar PV, if homeowners did their research on suitability and affordability, understands warranty periods and is working with qualified electrician then let them install the freaking solar PV and pay them for the damn electricity they export. Where is the harm in that! Ah wait, the 80% of MCS installers will have to sell their Porsches… Please be mindful of our community standards. Your email address will not be published.Required fields are marked *
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A massive solar tower in the Moroccan desert is the beacon of an ambitious push for a clean energy future. But fossil fuels and grid constraints stand in the way. The Moroccan city of Ouarzazate, about 200 kilometers (125 miles) southeast of Marrakech, lies on the edge of the Sahara and is known as the “door to the desert.” Ouarzazate is probably best known for the Atlas Film Studios, where blockbusters from “The Mummy” to “Gladiator” and “Game of Thrones” have been filmed. But a new industry is taking shape. Near the city, lying on a high plateau hemmed by the Atlas Mountains, one of the world’s largest solar power plants is being built. It is named Noor, meaning light in Arabic. Stretching over nearly 500 hectares (some 1,200 acres), the solar facility produces enough energy to power more than a million homes. But this is not a typical solar farm. Instead of commonly seen black PV panels, Noor uses concentrated solar power. A field of 2 million giant mirrors reflects the sun’s rays onto a central receiver that sits at the top of a 247-meter (810-foot) tower. The concentrated sunlight melts molten salt to 600 degrees Celsius (1,112 degrees Fahrenheit). That makes steam, which spins turbines, generating electricity even hours after sunset. In Ouarzazate, however, electricity remains expensive. Most households are not dependent on solar, but on butane gas. So why hasn’t clean energy arrived for the local community? One reason is that Morocco’s energy grid is still heavily reliant on fossil fuels, and especially coal-fired power generation. Intissar Fakir, a senior fellow and founding director of the North Africa and the Sahel program at the Middle East Institute in Washington D.C. said this has slowed the nation’s clean energy transition. “Fossil fuel-generated electricity contributes about 48% of the country’s energy-related greenhouse gas emissions,” she said. Moroccans spend around $110 (€94) of their $550 average monthly income on electricity. This is in a hot and dry country, where residents rely on air conditioning or a fan to stay cool. It’s regularly over 40 degrees Celsius in Ouarzazate during the summer, and the number of hot days and nights has roughly doubled in the region since the 1970s. This expense is partly down to the fact that Morocco does not produce any fossil fuels domestically, and imports about 90% of its coal, oil and gas, Fakir explained. Energy market and price fluctuations mean fossil fuel imports consume a major portion of the national budget, making the switch away from planet-heating coal, oil and gas increasingly urgent. That said, Morocco has made more progress on renewables than most North African countries. “Even by global standards, Morocco’s transition plan is pretty ambitious,” said Fakir. By 2030, the country plans to be able to power its economy with 52% of renewable electricity. By 2050, it’s aiming for 70% clean power capacity. And considering that the country has ample sun and coastal wind, the conditions seem right. The Noor solar plant might be the star of Morocco’s shift to renewables, but it’s just one of around two dozen solar, wind and hydro megaprojects already built. Another several dozen are in the pipeline. The country has also recently pledged to phase out coal power entirely by 2040 as part of its clean energy transition. But it has some catching up to do. While it currently has enough renewable technology to generate 46% of its electricity, in 2023 the nation only achieved a little over half of that. “The actual output in the country’s ability to integrate what Noor produces remains quite limited,” said Fakir. “Morocco still needs to invest in its grid capacity so they can integrate more of these renewable energies into daily use.” This includes investment in ways to store energy. She said more investment is also needed if the country is to realize its goal of selling its clean power abroad — especially to Europe. “Even as solar panels and wind turbines get cheaper, building large-scale, clean energy systems like Noor still takes serious upfront investment for low income countries,” she explained. Researchers and civil society organizations have also been critical of the government’s focus on megaprojects like Noor instead of more decentralized, small-scale clean energy schemes, including rooftop PV panels for homes, businesses and farms. One critique is that concentrated solar power is very water intensive. Its millions of mirrors need to be cleaned with water to remove sand and dust that get in the way of their ability to reflect light. In addition, a lot of grazing land was appropriated from local farmers to host Noor, with little consultation.
The project has divided locals, many of whom have seen few benefits. Imrane, an 83-year old resident, said electricity is still very expensive for villagers, adding that the solar tower’s mirrors and concentrated sunlight has driven up temperatures in their villages. Fakir said that, despite the expense, the Noor solar project was an experiment. “These are great flagship projects that prove the extent of Morocco’s technical capabilities,” she said. “But they also again highlight the challenge that even with these massive investments, renewables are still struggling to displace the entrenched coal and fossil fuel generation.” Edited by: Stuart Braun This article was adapted from a DW Living Planet radio series on solar energy. Click here to listen.
Solarport has launched the modular PowerPark PRO PV carport series, designed to meet UK/EU parking standards and adapt to various site layouts with multiple configurations and orientations. Image: Solarport
UK-based Solarport has unveiled this week a new PV carport line with modular design. “Solarport designed the PowerPark PRO Series to exceed the UK and EU parking space requirements, including disabled and parent-and-child bays, and to fully comply with the spacing standards outlined by the BRE National Solar Centre,” Thea O’Brien, Innovation Project Lead at Solarport, told pv magazine. “Its modular design allows the structure to scale from small installations to large car parks, providing businesses with a flexible solution that meets their unique project needs.” The series includes four different models, which the manufacturer said suit different site layouts and orientations. The M model is designed for sites with limited space and is available in two configurations: M2, 2-in-portrait, supporting modules up to 2,465 mm, and M3, 3-in-portrait, supporting modules up to 1,762 mm. Both are designed for south-facing systems with a tilt angle over 10°. The R variant is engineered to suit more complex or restricted site layouts and is available in the same two configurations as the M variants. The difference consists in allowing the deployment of solar modules with a tilt angle of less than 10°. The G model is claimed to be an ideal solution for east-west oriented car parks. It is is available in two configurations: G4, 4-in-portrait, and G6, 6-in-portrait, for a tilt angle of over 10°. The G4 variant supports module sizes up to 2,465 mm, while the G6 accommodates modules up to 1,762 mm. Moreover, Solarport offers the R2, 2-in-portrait, variant and and the R3 (3-in-portrait)—optimized for south-facing orientation with a structure angle of less than 10°. The R2 variant supports module sizes up to 2,465 mm, while the R3 accommodates modules up to 1,762 mm. All models are constructed using S275 hot-dip galvanized steel for primary components and S450 steel with ZM310 coating for sheet elements, ensuring durability and corrosion resistance. They also feature clamps and a back-to-back purlin rail configuration with three pairs per bay for secure module mounting. The design also supports installations on ground inclinations of up to 5°, offering flexibility for a wide range of site conditions, according to the manufacturer. Each structure accommodates bays up to 7.9 m, three standard car spaces, and extends to a maximum length of 63.75 m. The systems are also certified to withstand wind speeds up to 30 m/s and a snow load of 1 kN. The design also complies with multiple British and European standards, including BS EN 1991 and BS EN 1993 series. “This hasn’t been a product developed in isolation. Our innovation team has worked closely with clients throughout the process, making sure we’ve built something that reflects what the market is asking for. As with every Solarport product, it’s been shaped by real feedback, real projects, and real challenges,” the company said in a statement. 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. More articles from Emiliano Bellini Please be mindful of our community standards. Your email address will not be published.Required fields are marked *
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As of April 15, 2026, the global energy landscape is caught between two converging forces: a desperate, AI-driven surge in electricity demand and a volatile geopolitical struggle over the supply chains that power the renewable transition. At the epicenter of this conflict sits First Solar, Inc. (NASDAQ: FSLR), a company that has transformed from a niche technology player into the undisputed industrial champion of the American solar industry. While its competitors in the crystalline silicon space struggle with a massive global oversupply and razor-thin margins, First Solar has built a defensive moat reinforced by unique thin-film chemistry and an unprecedented level of U.S. government policy support. However, as the company navigates the middle of 2026, it faces a new set of challenges: a maturing tax-credit market, shifting political winds, and a technological race to maintain its efficiency edge against advanced silicon alternatives. First Solar’s journey began in 1999, but its roots trace back to the experimentation of Harold McMaster, a glass industry pioneer who saw the potential in Cadmium Telluride (CdTe) as a photovoltaic material. Unlike the crystalline silicon (c-Si) used by 95% of the industry, CdTe offered the promise of a continuous manufacturing process. The company’s early trajectory was fueled by the backing of the Walton family (of Walmart fame), through their investment vehicle, JTW Trust. This patient capital allowed First Solar to survive the “solar winters” of the early 2000s and go public in 2006. For years, the company operated as a dual-threat entity, both manufacturing modules and developing massive utility-scale power plants. The most significant transformation occurred under current leadership, which successfully pivoted the company away from project development to focus exclusively on being a “pure-play” module manufacturer. By shedding its engineering, procurement, and construction (EPC) business, First Solar de-risked its balance sheet and prepared itself for the massive manufacturing scale-up triggered by the 2022 Inflation Reduction Act (IRA). First Solar’s business model is defined by vertical integration and technological differentiation. The company manufactures thin-film solar modules that do not require polysilicon, the key raw material for most solar panels, which is largely controlled by Chinese supply chains. Revenue Streams: The “Glass-to-Module” Process: First Solar’s manufacturing is unique in its speed. It can transform a sheet of glass into a finished, functional solar panel in roughly four hours within a single facility. This “integrated” model contrasts with silicon competitors, who often move products through four or five different factories across different countries (ingot, wafer, cell, and module stages). Over the last decade, First Solar has been a barometer for the solar industry’s booms and busts. As of today, April 15, 2026, the stock trades at $203.47, reflecting a market that is balancing First Solar’s massive backlog against broader macroeconomic uncertainty. First Solar’s recent financials showcase a company enjoying record profitability, though 2026 represents a year of intensive reinvestment. Mark Widmar (CEO): Widmar has been the architect of First Solar’s current “discipline-first” strategy. Known for his conservative guidance and focus on the balance sheet, he has resisted the urge to engage in price wars with Chinese manufacturers. His strategy focuses on “booking to fill”—securing a backlog that stretches several years into the future to ensure manufacturing stability. The Management Philosophy: The leadership team is praised for its “U.S.-first” manufacturing approach, which has aligned the company’s corporate goals with U.S. national security and energy independence goals. This has given First Solar a seat at the table in Washington D.C., influencing trade policy that protects its market share. The flagship product in 2026 is the Series 7 module. Manufactured in Ohio, Alabama, and Louisiana, the Series 7 is designed specifically for the U.S. utility-scale market. It features a larger form factor and a galvanized steel back-rail that significantly reduces installation time—a major selling point for developers facing labor shortages. The Innovation Pipeline: To stay ahead of high-efficiency silicon competitors (like TOPCon cells), First Solar is betting on Tandem Cell technology. By layering its traditional CdTe with a material called Perovskite, the company aims to break the 25% efficiency barrier. The company’s R&D hub in Ohio is currently scaling this technology for commercial release in the 2027-2028 timeframe. The primary competition comes from Chinese silicon giants such as JinkoSolar (NYSE: JKS), LONGi, and Trina Solar. The most significant trend of 2026 is the AI Power Crunch. Data centers for companies like Microsoft (NASDAQ: MSFT) and Google (NASDAQ: GOOGL) require massive amounts of 24/7 carbon-free energy. This has led to a shift where big tech companies are signing multi-gigawatt deals directly with developers who use First Solar modules, viewing them as the most “bankable” and “geopolitically safe” choice. Additionally, “reshoring” remains a dominant macro theme. The U.S. is increasingly treating solar manufacturing as a strategic industry, similar to semiconductors, which provides a long-term tailwind for domestic producers. Wall Street remains “cautiously bullish.” As of April 2026, there are 22 “Buy” ratings, 8 “Hold” ratings, and 1 “Sell” rating on the stock. Institutional ownership remains high, with Vanguard and BlackRock holding significant stakes. Hedge funds have recently used the February 2026 price dip to add to positions, betting that the AI-driven demand for solar is still in its early innings. Retail sentiment is more mixed, often reacting to the volatile swings caused by political headlines regarding green energy subsidies. First Solar is perhaps the most “policy-leveraged” stock in the S&P 500. First Solar in 2026 is a company that has successfully traded the volatility of the global commodity market for the stability of a policy-protected domestic powerhouse. With a backlog that covers production through the end of the decade and a net cash position that is the envy of the industry, the company is fundamentally stronger than it has ever been. However, for investors, the story is now about execution and policy durability. Can First Solar successfully bridge the gap to next-generation tandem cells before its tax credits begin to phase out in the 2030s? And can it survive the cyclicality of American politics? For now, First Solar remains the indispensable player in the American energy transition, standing as a rare example of a U.S. manufacturing success story in the high-tech renewable space. This content is intended for informational purposes only and is not financial advice.
Droplets of rain are seen scattered on the brand new solar panels Monday, April 12, 2021 outside the Pennsylvania Turnpike’s Greensburg maintenance facility in Hempfield. (Shane Dunlap | TribLive) Westmoreland County Airport Authority members on Tuesday authorized an Arizona-based energy company to proceed with plans for a scaled-back project to install a solar farm at Arnold Palmer Regional Airport in Unity. It’s a project officials said will provide power for an expanded passenger terminal and potentially could generate additional revenue over the next two decades. The $4.4 million proposal is a significant departure from an initial project unveiled in February to install solar panels at both the Palmer airport and the county’s smaller airport in Rostraver. That $30 million project also included installation of solar panel canopies covering more than 600 paid parking spots at the Palmer airport. A smaller proposal was pitched in March that limited the solar panel canopy installation for just the 138 parking spots at Palmer airport. That option was tabled after board members learned the authority could incur nonrefundable costs, up to $10,000 annually, associated with borrowing of money to pay for the $4 million project. Veregy senior account manager Mitch Dexter on Tuesday proposed another revised $4.4 million plan to install traditional ground-based solar panels on airport property that he said would provide up to 95% of the current airport terminal’s power needs. “We anticipate this will generate about $1.5 million in additional revenue (for the authority) over 20 years,” Dexter said. The project, he said, could produce 150% more power than envisioned by the installation of solar canopies. That plan was unanimously approved Tuesday by the nine-member authority board. Veregy’s initial pitches required the authority to pay for initial engineering and planning. No outlay of funds will be needed to pay for the early planning of the scaled-back proposed solar farm, Dexter said. The authority will need to come up with the money, likely through borrowing, to install the solar panels once the final project plans are completed and permitting is approved. As part of the plan, the authority will seek about $1.6 million in federal subsidies for the proposed solar farm, officials said. Authority board chairman Paul Whittaker declined to discuss the project following Tuesday’s public meeting, saying only, “I voted for it.” Categories Directory
The nation’s latest call for long-term power purchase agreements focuses on supplying the national grid with wind and solar projects, specifically mandating integrated battery storage systems to ensure grid resilience. Image: CUED From pv magazine Latam The Dominican Republic and its Unified Council of Distribution Companies (CUED) has unsealed the financial bids for a major public tender aimed at integrating up to 600 MW of new renewable generation into its national grid. The procurement process stands out by demanding firm capacity and grid stability through mandatory energy storage. Officials reviewed 20 proposals from qualified developers seeking to build utility-scale wind and solar photovoltaic farms ranging from 20 MW to 300 MW. The process aims to integrate new renewable capacity to meet the energy demands of the North, South, and East regional distribution networks. The tender had the mandate that all participating projects must incorporate four-hour duration battery energy storage systems (BESS). According to the tender’s specifications, each awarded long-term power purchase agreement (PPA) must become operational within 24 months of signing. The contracted energy will be allocated among the regional grids as follows: North 30%, South 35%, East 35%. During the bid unsealing, Dominican energy officials emphasized the broader strategy of diversifying the national energy mix. The country has already achieved a 25% renewable energy share within its national interconnected grid, with a targeted milestone of 30% by 2030. They also stressed the importance of keeping the bidding process highly competitive to drive down costs. Initially launched last August, the tender has attracted significant global interest, with 32 international and regional companies presenting credentials late last year. To attract foreign investment, the long-term PPAs will be settled in US dollars and backed by end-user tariffs, offering a secure, bankable revenue model for developers willing to meet the rigorous energy storage requirements. 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. More articles from Luis Ini Please be mindful of our community standards. Your email address will not be published.Required fields are marked *
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National residential solar installer Freedom Forever has filed Chapter 11 bankruptcy in Delaware. The company was the top residential contractor on the 2025 Top Solar Contractors List, based on kilowatts installed. Freedom Forever listed its estimated assets between $100 million and $500 million. The company’s estimated liabilities are between $500 million and $1 billion. Mosaic…
Oman’s Naqaa Sustainable Energy LLC is set to design, finance, construct and operate a 500 MW solar project in northwestern Botswana. A groundbreaking ceremony is scheduled to take place later this week. Image: Duma Gideon Boko/Facebook Botswana’s President, Duma Boko, has announced he entered into an agreement with the Sultan of Oman, Haitham bin Tariq, for the development of a 500 MW solar project with battery storage. Reports from Reuters state that Oman’s NAQAA Sustainable Energy LLC, a subsidiary of state-owned renewable energy company O-Green, has been selected to design, finance, construct and operate the solar project. Set to be located in the town of Maun within Botswana’s northwestern region, the project is expected to have a minimum operational life of 25 years. President Boko has posted on social media that a groundbreaking ceremony will take place for the project on April 16. He added that the solar project will allow the country to secure its energy future and unlock long-term economic value. Botswana currently has 181.5 MW of operational solar, according to the Africa Solar Industry Association’s (AFSIA) project database. The country is targeting a 50% contribution from renewable sources to its national energy mix by 2030, up from around 8% today. 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. More articles from Patrick Jowett Please be mindful of our community standards. Your email address will not be published.Required fields are marked *
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GAIL (India) Ltd, India’s leading natural gas company, has approved the setting up of 700 MW of solar power projects for captive consumption, with an investment of INR 3,800 crore, in the states of Uttar Pradesh and Maharashtra. GAIL GAIL (India) Ltd, India’s leading natural gas company, has approved the setting up of 700 MW of solar power projects for captive consumption, with an investment of INR 3,800 crore, in the states of Uttar Pradesh and Maharashtra. As part of this initiative, it will develop a 600 MW solar power project along with a 550 MWh battery energy storage system (BESS) at TUSCO Solar Park Jhansi in Uttar Pradesh. The project will primarily cater to the captive energy requirements of GAIL’s Petrochemical Plant at Pata in Auraiya district. In addition, the company will set up a 100 MW solar power project with a 22 MWh BESS in Chhatrapati Sambhaji Nagar district (formerly Aurangabad) in Maharashtra. This facility will mainly serve the captive requirements of GAIL’s PDH-PP Plant at Usar in Raigad district. Deepak Gupta, chairman & managing director, GAIL, said, “GAIL’s installed renewable energy capacity shall increase substantially to over 1,000 MW from the current 147 MW upon commissioning of these projects.” He added that this expansion underscores GAIL’s strategic vision of aligning its growth trajectory with environmental responsibility while ensuring long-term energy security. 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. More articles from Uma Gupta Please be mindful of our community standards. Your email address will not be published.Required fields are marked *
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The world’s largest wind–solar co-located project is now operational on the Loess Plateau in northwest China, marking a significant milestone in the evolution of large-scale renewable energy systems. With a total installed capacity of 6 GW, made up of 4.5 GW of wind and 1.5 GW of solar, the project delivers more than 12 TWh of green electricity annually. This clean power is transmitted via ultra-high-voltage (UHV) lines to key industrial regions along China’s eastern coast, helping to decarbonise some of the country’s most energy-intensive areas. What makes this achievement particularly remarkable is not just its scale, but the complexity of its environment. The Loess Plateau, characterised by rugged valleys, desert fringes, and highly variable wind conditions, presents formidable logistical and engineering challenges. Limited construction windows and difficult terrain demanded a highly coordinated, efficient, and adaptive approach to execution. Envision Energy, who supplied the turbines, addressed these challenges through three core capabilities: Tailored turbine and technology solutions The deployment of customised EN-200/5.56 MW turbines was central to the project’s success. Designed specifically for low-wind, mountainous environments, these turbines feature larger rotors and higher capacity, enabling greater energy capture while reducing the total number of turbines required. This not only streamlined installation but also accelerated overall project delivery. Advanced supply chain and organisational execution Executing a project of this scale in such terrain required seamless coordination across multiple manufacturing and logistics hubs. Envision Energy orchestrated the transport of massive 99-meter blades through narrow, winding mountain roads—an operation demanding precision planning and real-time coordination. This capability ensured that materials and components arrived on-site efficiently, minimizing delays. Extreme-condition delivery capability To meet tight construction timelines, the project implemented a 1:1 allocation of transport and lifting equipment per turbine. This allowed for continuous installation over an approximately 150-day window. Additionally, single-blade installation techniques enhanced flexibility and efficiency, particularly in constrained or uneven terrain. Once considered a harsh and resource-limited region, the Loess Plateau is now being redefined as a cornerstone of China’s renewable energy future. This project not only demonstrates what is technically possible but also sets a new benchmark for integrated, large-scale clean energy deployment in challenging environments. Your email address will not be published.Required fields are marked *
A new report from Metal Focus reveals that global silver market remains structurally tight, with elevated prices, a fifth consecutive annual supply deficit in 2025, and ongoing mine and recycling constraints despite modest production growth. At the same time, PV-driven silver demand is falling sharply due to cost pressure and thrifting. Silver metallization paste Image: Heraeus The global silver market remains structurally tight despite weakening demand from the photovoltaic sector, with elevated prices and constrained supply continuing to shape the PV manufacturing landscape. According to the latest World Silver Survey 2026 by independent research consultancy Metals Focus, silver prices rose sharply through 2025, averaging just over $40 per ounce, a 42% year-on-year increase, before climbing to even higher levels in early 2026. The rally was driven by a combination of strong investment demand, tightening physical supply, and ongoing geopolitical and macroeconomic uncertainty. At the same time, the solar sector, long a key driver of industrial silver demand, is entering a period of adjustment. Silver demand from PV producers declined by 6% in 2025 to 186.6 million ounces and is now forecast to fall by a further 19% in 2026 to around 151 million ounces. “Industrial offtake slipped by 3% to 657.4 million ounces, marking the first post-pandemic decline, as a contraction in PV demand and thrifting elsewhere outweighed gains linked to AI-related data-centers, high-speed transmission hardware, EV penetration and charging infrastructure,” the report reads. The decline in PV-related silver consumption reflects a combination of technological change and cost pressure. As silver prices increased, module manufacturers accelerated efforts to reduce silver loadings per cell by adopting thrifting strategies and alternative metallization approaches. The analysts explained that intense competition and rising raw material costs have pushed producers to cut silver usage, even as global solar installations continue to grow, noting that this growing decoupling between PV capacity expansion and silver demand marks a significant shift for the industry. On the supply side, global silver mine production rose significantly last year, supported by mining project ramp-ups in Latin America. Recycling also increased modestly, reaching a 13-year high of 197.6 million ounces. Despite these positive results, the silver sector recorded its fifth consecutive annual deficit in 2025, totaling 40.3 million ounces, with another shortfall expected in 2026. Structural constraints, including declining ore grades, operational disruptions, and a limited pipeline of new projects, are expected to continue limiting supply growth. Recycling volumes are rising but remain constrained by refinery bottlenecks and capacity challenges. The report also reveals that, while PV demand weakened, other segments such as AI-driven data centers, electric vehicles, and power infrastructure continued to support consumption. Looking ahead, total industrial demand is expected to decline again in 2026, with further weakness in PV outweighing gains in emerging applications. Silver, however, is expected to remain a strategic material risk for PV manufacturers, even as technological innovation continues to reduce dependence on the metal. According to recent analysis by the Silver Institute, the photovoltaic industry is expected to use less silver in 2026. Silver paste currenly accounts for around 10-20% of total solar cell costs, creating a difficult environment for manufacturers already facing overcapacity, falling module prices and squeezed margins. 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. More articles from Emiliano Bellini Please be mindful of our community standards. Your email address will not be published.Required fields are marked *
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Constructing solar projects on commercial buildings without penetrating the roof surface is commonly achieved with ballasts, but some mounting companies have developed other methods to securing these arrays without penetrations. Ballasts are the industry standard for securing solar projects to flat commercial rooftops. Typically, concrete blocks are placed on flat trays attached to racking to…
The growing availability of financing options has had a visible impact on solar adoption. States with well-developed financing ecosystems and supportive policies have recorded significantly higher growth in rooftop installations. In some regions, adoption rates have increased multiple times within a short period. A 4.8 kW rooftop plant in Bangalore running on AXITEC N-type TOPCon modules AXITEC India’s clean energy transition is often discussed in terms of ambitious capacity targets and rapid solar deployment. However, an equally significant transformation is taking place in the background — the evolution of financing mechanisms that are making solar energy more accessible and economically viable across consumer segments. Over the past decade, India’s installed solar capacity has grown to approximately 85–90 GW, positioning the country among the world’s leading solar markets. Within this, rooftop solar installations account for an estimated 11–13 GW. While this growth has been substantial, it represents only a fraction of the country’s long-term ambition. India has set a target of achieving 500 GW of non-fossil fuel capacity by 2030, with solar energy expected to contribute around 280–300 GW. Achieving this scale will require not only continued policy support and technological advancement but also a robust and inclusive financing ecosystem capable of supporting widespread adoption. Historically, one of the primary barriers to solar adoption has been the high upfront cost. Residential rooftop systems typically require an investment ranging from INR 2 lakh to INR 5 lakh, making them inaccessible to a large section of households and small businesses. As a result, adoption has been skewed toward the commercial and industrial (C&I) segment, which accounts for nearly 70–75% of rooftop installations. These consumers possess the financial capacity to make long-term investments and benefit from energy cost savings over time. However, this concentration has also highlighted the need for more inclusive financing solutions. Government intervention has played an important role in improving affordability. The PM Surya Ghar: Muft Bijli Yojana, launched to accelerate residential rooftop adoption, offers subsidies of up to 40% for eligible systems and aims to benefit nearly one crore households. The scheme has a total outlay of approximately ₹75,000 crore, reflecting the scale of policy commitment toward distributed solar. While such initiatives reduce upfront costs, subsidies alone are insufficient to unlock mass adoption. The broader shift is being driven by innovative financing models that address the affordability challenge more directly. In recent years, the Indian solar market has witnessed the rapid adoption of alternative financing structures: OPEX and Pay-as-you-go Models: These allow consumers to avoid upfront investment by paying only for the electricity generated. Third-party developers own and operate the systems, making this model particularly effective for commercial users. RESCO (Renewable Energy Service Company) Model: Under this framework, developers install and own the solar asset while selling power at a pre-agreed tariff. This provides consumers with predictable savings and minimal operational responsibility. Solar Loans and EMI-Based Financing: Banks, non-banking financial companies (NBFCs), and fintech platforms are increasingly offering tailored loan products for solar installations. In many cases, monthly EMI payments are comparable to or lower than existing electricity bills. Leasing and Subscription Models: These models enable users to access solar systems without ownership, reducing financial risk and simplifying adoption, particularly in urban markets. Digital Financing Platforms: Technology-driven platforms are streamlining the financing process by integrating system design, loan approval, and installation services, thereby reducing timelines and improving transparency. The growing availability of financing options has had a visible impact on solar adoption. States with well-developed financing ecosystems and supportive policies have recorded significantly higher growth in rooftop installations. In some regions, adoption rates have increased multiple times within a short period. Moreover, solar energy is increasingly being perceived not merely as an expense but as a long-term investment. With payback periods typically ranging between four and six years, consumers are able to recover their initial investment relatively quickly, after which electricity generation effectively becomes cost-free. Despite these advances, several challenges continue to constrain the full potential of solar financing in India. These include limited consumer awareness regarding available financing options, complex documentation processes, perceived credit risks — particularly in the MSME segment — and delays in subsidy disbursement. Additionally, a lack of standardization across states and financing institutions creates inconsistencies in implementation. Addressing these issues will be critical to ensuring sustained growth, particularly in rural and semi-urban markets where adoption remains relatively low. India’s solar financing landscape is expected to evolve further as the market matures. Emerging trends such as embedded finance, AI-driven credit assessment, and integrated financing solutions for solar-plus-storage systems are likely to shape the next phase of growth. Industry estimates suggest that the solar financing opportunity in India could reach INR 8–10 trillion over time, underlining the scale of untapped demand. Ultimately, the success of India’s solar transition will depend not only on how much capacity is installed but also on how easily consumers can access and finance that capacity. Financing, therefore, is no longer a supporting component of the solar ecosystem — it is becoming one of its central pillars. As innovative financing models continue to lower entry barriers and expand access, solar energy is steadily moving from being an alternative energy source to becoming a mainstream solution for India’s power needs. The views and opinions expressed in this article are the author’s own, and do not necessarily reflect those held by pv magazine. 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. Please be mindful of our community standards. Your email address will not be published.Required fields are marked *
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The company driving two of Australia’s largest renewable energy projects has announced key milestones for the system architecture that is to serve as the backbone for the proposed giga-scale green hydrogen projects. Image: Intercontinental Energy InterContinental Energy (ICE) announced it has secured up to $1.6 million (USD 1.14 million) in federal government funding to develop a digital twin for its P2(H2)Node (power to hydrogen node) that is designed to provide standardised architecture for large-scale green hydrogen production projects. The Perth-based company said it has also signed the first licence for the modular system architecture, which will see the node deployed on an as-yet unidentified “large-scale renewable hydrogen project.” While ICE did not identify the licence holder, the company’s head of engineering and innovation, Richard Colwell, said the agreement will provide an early reference case for the P2(H2)Node, paving the way for further agreements with developers globally. “This first licence is a significant milestone, moving the node from concept to deployment,” he said. “We expect it to serve as a model for future licences, enabling developers to use a proven, optimised design rather than starting from scratch.” The patented P2(H2)Node system is engineered to directly integrate giga-scale hydrogen production with large-scale solar and wind farms, eliminating long-distance transmission, cutting costs and boosting efficiency. ICE has estimated that the modular architecture will cut capital expenditure by up to 10% and boost operational efficiency by as much as 10% compared to conventional hydrogen production models. The company is now working to develop a standardised digital twin and licensable engineering design for the node after securing up to $1.6 million in funding from the Australian Renewable Energy Agency (ARENA) under its Advancing Renewables Program. ICE said ARENA’s support will help create a Digital Twin Optimisation Framework that developers can use to plan large-scale green fuel hubs. Colwell said standardising and simulating the nodal architecture across varying technology and site parameters, the framework will help developers plan renewable hydrogen projects with greater certainty on cost, performance and delivery timelines. “We are advancing digital and engineering design work that gives developers and investors more certainty on cost, performance and timing, at a time when fuel security and AI power needs are front of mind,” he said. The P2(H2)Node architecture, now patented in more than 50 countries, is set to serve as the mainstay of the proposed 70 GW Western Green Energy Hub (WGEH), being developed in southwest Western Australia by ICE in collaboration with CWP Global and Mirning Green Energy. Image: Western Green Energy Hub Pty Ltd Spanning 15,000 square kilometres, the WGEH would include up to 70 GW of solar and wind generation developed in stages to power electrolysers to produce up to 3.5 million tonnes of green hydrogen annually for both domestic consumption and export, positioning it among the largest green hydrogen projects in the world. ICE recently announced that it has secured enough green ammonia offtake interest from Japanese and Korean customers to support an initial stage that would deliver a minimum 1.4 million tonnes per year online in 2033, which would be followed by subsequent phases until the full planned capacity is reached by 2050. The developers have also signed a feasibility phase agreement with Chinese heavy equipment manufacturer Sany International Development and South Korean entities to advance Stage 1 development of the project. The agreement enables full feasibility and pre-FEED studies for Stage 1, which targets approximately 6 GW of solar and wind capacity producing up to 330,000 tonnes per year of green hydrogen. ICE is also developing the Australian Renewable Energy Hub (AREH), a 26 GW solar, wind, and green hydrogen project planned for Western Australia’s Pilbara region. At full scale, AREH could produce up to 1.6 million tonnes of green hydrogen. 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. More articles from David Carroll Please be mindful of our community standards. Your email address will not be published.Required fields are marked *
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Loading weather forecast… Today Post Courier Papua New Guinea's 'trupla' leading Daily Newspaper Since 1969.The Post-Courier is proud of its record as the voice of PNG. We were there when the nation took its first bold steps towards independence. Since that time, we have fearlessly recorded the nation's progress. The Napa Napa Solar Farm project is the largest of its kind in Papua New Guinea. It was successfully commissioned on Tuesday April 14, 2026 which signified a major milestone and a new dawn in the PNG energy sector. The project took 12 months to complete and worth about K52 million is a clear demonstration of what private initiative, proper process and strong partnership can deliver for PNG.
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