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Scientific Reports volume 16, Article number: 8718 (2026)
872
5
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The full potential solar photovoltaic (PV) energy is not utilised by the mining industry due to heavy dust deposition and harsh operating condition. This study aims to quantify the seasonal impact of dust deposition on PV performance and determine the optimal cleaning frequency for optimize the performance of solar PV Panel in an operational mining condition. Additionally, an innovative automated dry dust cleaning system is designed, developed, and validated in the active mining field to evaluate its operational efficiency and durability. A comprehensive study of twenty-six week was conducted to monitor the variations in dust deposition density and output energy of PV panel across three distinct seasonal phases. Among these, pre-summer phase showed the highest dust deposition density of 5.98 g/m2 and due to this maximum output power (Pmax) of dusty panel reduce by 63.50%. This phase experienced an intense mining activity and dry weather condition. Therefore, a cleaning schedule of 3 to 4 days is recommended to effectively utilise the potential of PV panel. The other two phases such as dry winter and early monsoon experienced comparatively lower average reduction of 35% to 40% in maximum output power. A moderate cleaning scheduled of 6 to 7 day is recommended for these two phases Further, the developed dust cleaning system is validated in the mining field under three different environmental phases and an average recovery of 40% in Pmax is obtained across three phases. This presents the effectiveness of developed dust cleaning system under real operating condition. The outcome of this research highlights the need of dynamic cleaning schedule for effective utilisation of solar energy in mining industry. The integration of smart dust sensors and AI based predictive modelling of developed cleaning system for sustainable utilisation of solar energy in mining and allied industries.
The mining industry is the backbone of the country economy that includes energy intensive operations. These operations receive energy from conventional grid and diesel operative power generation which is not a sustainable solution. Therefore, there is an urgent need for sustainable energy solutions for powering the operation of mining industry. Solar PV panels emerges as a alternative solution that only full-fill the energy demand of mining industry but also reduces its carbon foot print1,2. Solar based power solution enables the mining operations to meet global decarbonization goals. The effective integration of solar energy in the mining industry supports would be able to full-fill all its energy demand. This not only promotes green mining initiative but also provides a decentralised uninterrupted mining operation. As a result, efficiency of mining industry can be increased while maintain its commitment towards sustainable growth. The introduction of solar PV based energy emits zero emission during its operation and lowers long-term costs3,4. The full potential of solar PV energy can not be utilised due dusty and harsh operating condition. Mining industries generally located in remote locations which experienced a seasonal variation, higher dust generation and dynamic operating conditions5,6,7. These operational parameters reduce PV panel performance significantly mainly due to the deposition of thick dusty layers which is produces due to heavy machinery operations. This demotivates the deployment of solar PV system in mining industry. This deployment issue is not just a technical challenge but is also logistically complex5,6. Therefore, for smooth operations there is a need of strategic planning which can tackle dust deposition problem and improves the performance of solar panel under high dusty locations6,8,9.
Mining industry is one of the challenging sites for effective utilisation of solar PV energy. This is mainly due to its harsh climates, extreme temperatures, and dust surroundings. These issues are the main obstacles for the effective deployment of solar PV systems. Mining industry produces higher rate of dust pollutants than any other industry. Dust play a major role in reducing the PV panel performance thus managing the dust deposition can optimise the panel performance in mining environment. In mining industry, the continuous operation of heavy machinery and constant excavation activities such as drilling, blasting, and hauling exacerbate dust generation that leads to higher deposition over the panel surface10. This can cause short-term energy loss and long-term damage to the surface of PV panels. The excess generation of dust reduces the optical transmittance of panel glass consequently lowers generation of electric charges form PV panel. This reduces the performance of solar PV panel in harsh dusty condition which indicates more cleaning operation that increase the maintenance costs and reduce the life span of the solar panels11,12,13,14,15. Thus, an effective dust control measures can improves the panel performance which allows the panel to operate in its full potential.
Previous studies reported a significant performance degradation of solar PV panel in dry and dusty industrial zones. One study reports the reduction of 20% to 60% in output power of solar PV panel16. The variation of performance degradation under dusty environment depends on dust type, location, and panel installation angle. Previous studies present various predictive model of solar PV performance against different operating parameters namely dust density, solar radiation, temperature, and humidity. The operating parameters like solar radiation, temperature and humidity affect the dust deposition density over the panel surface. The performance predictive model provides useful insights and environmental sensitivities that promotes the effective utilisation of solar energy in mining industry. Most of these models are simulation-based and lack of data validation. Thus a comprehensive study of panel performance under real mining condition needs to be performed17,18,19,20,21.
Mining industry shifting its energy dependency from fossil to non-fossil fuels based energy sources like solar PV. In recent time, huge capacity of solar PV is installed in various coal and metal mines in the country. These installed panels continuously experiencing the drop in its performance. Dust accumulation is major reason for reducing panel performance under high dusty condition of mining industry. This needs a frequent dust removal maintenance which increases the cost of operation. Therefore, it is necessary to optimize its cleaning cycle that enhance its performance under high dusty environment. Although several cleaning approaches like manual, semi-automatic, and robotic have been developed but most of these are optimized for urban or residential contexts. Very limited studies address this unique challenges under harsh mining conditions. A mining industry provides a dynamic operating condition through continuous excavation, hauling, and crushing activities. These activities generate significant amount of dust that creates a adhesive dust layers over the panels surface. Mining dust differs from typical environmental particulates: it is coarser, more metallic, and forms a persistent film that resists conventional cleaning. If these layers are not cleaned at regular intervals, they may form permanent dark spots on the panel surface. This not only reduces the PV panel’s performance but also shortens its operational lifespan. Presently, water-based cleaning is more popular in mining areas which is not a sustainable cleaning solution. Therefore, there is a need to develop an alternative approach of cleaning the panel surface so that its performance can be improved under dusty condition. Further, there is a need to determine the optimum cleaning time for mining industry because under and over cleaning disturb the operating efficiency of PV panel. Moreover, earlier studies predominantly relied on controlled laboratory tests or static setups that do not reflect the real dynamics of mining environments. Therefore, it is essential to examine in situ PV performance under actual field conditions using innovative cleaning techniques and to determine optimized cleaning intervals. These two aspects are critical for improving energy yield and maintenance planning in industrial solar energy systems.
To bridge the existing knowledge gap, this study introduces a novel field-based framework for determining the optimized cleaning interval of solar PV panels operating under mining dust exposure. This study aims to design and implementation of an automated dust cleaning system that enable periodic removal of deposited particulates from PV panel surface. The designed cleaning system is validated under real operating mechanized iron mines which is located in the southern India. A detail field investigation is performed to evaluate the efficiency of solar PV panel that address the impact of dust deposition and optimize cleaning frequency on the panel performance. The key electrical parameters such as short-circuit current (Isc), open-circuit voltage (Voc), and maximum power output (Pmax) were considered during analysing the panel performance under dusty condition. This study establishing a direct link between automated cleaning efficiency and real-world performance recovery of solar PV panel under challenging mining condition. A developed dust cleaning system offers a cost-effective, waterless, and no human indentation which is specifically engineered for harsh mining environments. By combining field-scale validation and optimise cleaning frequency addresses scientifically rigorous and practically scalable framework for enhancing the performance, reliability, and sustainability of solar PV systems in dust-intensive mining operations.
Rapid industrialization and urbanization are the main cause of airborne dust pollutants22. These particles settled on the panel surface and create a thick layer of dust deposition that attenuates a significant amount of sun light to penetrate the glass surface23,24. The degree of this attenuation depends on several factors, including the size, density, and type of dust particles. Finer dust particles can diffuse sunlight more effectively, while larger or denser dust clusters block sunlight directly25,26. As a result optical transmittance of panel glass reduces under the high deposition of dust over its surface. Thus, the performance of solar PV Panel often degrades considerably in dusty and industrialized areas27,28,29. Mining industry is considered as one of the highest contributors of air pollution. Due to higher generation of dust solar PV panel does not perform at its full potential. This layer of dust attenuates incoming sunlight, significantly reducing energy conversion efficiency. Type of dust deposition also affect the performance degradation. One study recorded the reduction in solar PV energy of 19%, 10%, and 6% for the deposition of red soil, limestone and ash respectively30. In one of the study deposition of ash dust over the panel surface showed more reduction in its performance when compared to other deposited pollutants like red soil, sand, calcium carbonate, and silica gel. The study reported the minimum reduction of 0.9 V to maximum reduction of 4.7 V in output voltage of PV panel due to different deposited dust pollutant31. Further, a same level of dust deposition offers the different performance degradation for two different technologies of solar PV panel. A study demonstrated the different in monocrystalline PV panel showed lesser performance degradation than multi-crystalline under same level of dust deposition density. This is mainly due to the quality of silicon that decides the panel performance under expose environmental conditions32. A study showed the lesser reduction of 4.1% in short circuit current of monocrystalline panel compared to 4.79% and 7.34% for polycrystalline and amorphous silicon respectively33.
To effectively utilise the potential of solar PV panel there is a need of robust dust cleaning techniques particularly when panel installed around high-dust zones like mining industries. In recent time, different cleaning techniques are reported to over the problem of dust deposition over the panel surface. Water based cleaning mix with detergent is the most common practice for cleaning PV surface for small scale installation34. This methods not suits for large scale industrial installation due to its high demand of water and manual intervention. Thus, it not a feasible dust cleaning solution for arid and mining regions where water availability is limited. Additionally, the more usage of detergent chemically impact the optical properties of the glass by leaving chemical residue on its structure. Due to this physical structure of panel degrades at faster rate that reduces its end of life (EoL)35,36. Moreover, manual cleaning introduces operational downtime and safety risks for maintenance personnel, especially in elevated or hard-to-reach installations. The water cleaning technology disturb the panel performance by promoting micro-cracking due to thermal shock during rapid interaction of cold water with hot panel surfaces. The frequent application of the water on the panel glass degrades its mechanical strength. Thus, this method is not a feasible solution for larger installations. For larger installations, high-pressure water jets in combination with brushing have been reported an effective cleaning method. This study noted a significant improves the panel performance when compared to traditional water-based cleaning. in output power following such cleaning regimes37,38,39. One study demonstrated that manual cleaning with a water brush system led to a significant increase in output power for a PV plant, offering a unique solution to the advancement of solar PV systems40,41. However, these methods are not cost effective solution as it need a labour intensive job. This may provide an impractical solution in remote or water-scarce environments which is general scenario in many mining regions. Further, the application of high-pressure water jet may damage the glass integrity consequently its optical properties gets reduce. Therefore, there is a need of innovative cleaning technology that provides more feasible and environmentally friendly approach. A good cleaning system is one which provide minimal environmental footprint and reduced maintenance effort to optimise the panel performance.
Electrostatic dust cleaning is one of the innovative approaches for promoting dry cleaning that uses a series of alternating electrodes. These electrodes are embedded in a transparent dielectric film on the panel surface that charged the dust particles. These charged dust particles repel each other that supports the removal of dust deposition form the panel surface. This offers a solution that clean the panel surface without water and any moving parts42,43. But this technology suffers with its low dust removal rate that makes it a least effective under dusty operating environment. Further, due to rapid advancement of electronic components and accessories automatic operations becomes more popular. Automatic cleaning system provides a viable environment friendly approach to recover the performance of dusty solar PV panels. These systems typically use computer-controlled mechanical devices to automate the surface cleaning operation and are considered more efficient and reliable than manual methods. The automated dust cleaning system reduces labour and water consumption costs this makes it more suitable for large scale installation. A study conducted by Tejwani and Solanki (2010) showed an improvement of 15% in output power of dusty panel due to the integration of automatic dust cleaning system44.
Earlier studies on automated and electrostatic cleaning systems showed promise for performance recovery. However, most were done in controlled labs or small residential-scale conditions. These systems usually assume that dust is uniform, conditions are stable, and there is little mechanical stress. But these assumptions often fail in mining environments. In mines, dust is highly heterogeneous, abrasive, and dynamically deposited due to excavation and haulage activities. This makes most of the earlier designs unsuitable for long-term deployment. Furthermore, prior works rarely examined the optimization of cleaning frequency45,46. The optimize cleaning is an important parameter that affect the cost of cleaning system. Due to dynamic and harsh operating environment there is a need of conducting scientific study that can able to address the proper cleaning cycle. This technique results in lowering the excessive energy consumption and minimizing inefficient cleaning schedules. As the technology is enhancing there is potential of implementing robust sensor based cleaning mechanism that can able to operate in synchronous manner with reference to its cleaning cycle47.
Despite the advances cleaning technologies, limited attention has been given for determining the optimal cleaning frequency under real mining conditions. The determination of optimum cleaning is a necessary parameters as the dust generation is continuous and highly variable. Cleaning too frequently leads to unnecessary operational costs and energy use, while delayed cleaning results in severe performance degradation. Hence, defining an optimal interval is essential to balance efficiency, resource use, and maintenance effort. This analysis provides a site-specific optimized cleaning frequency that maintain the performance of solar PV under harsh operating environments like mining industry. To bridge this present study showed the seasonal performance degradation of solar PV panel in a mechanized iron mine located in southern India. The study highlight the effectiveness of automatic dust cleaning system that validated under real operating mining condition. The study provides the quotative degradation of panel performance under considered mining site that help in deciding the optimum cleaning time. This optimum cleaning mechanism not only improves the panel performance in long run but also improves the structural integrity. The field validation of developed sensor-assisted dry cleaning system highlights the effective utilisation of solar PV energy system in harsh operating mining conditions. It provides useful insights to improve solar energy use in tough industrial settings.
The study conducted in a mechanised surface iron ore mines located in Chitradurga District of Karnataka State with geographical coordinate of 14° 8’ 55.4928’’ N, 76° 40’ 1.1424’’ E. This site presents both favourable and unfavourable condition of effective utilisation of solar PV. The favourable operating condition offers high average solar radiation and good climatic condition throughout the year. In any sunny days a maximum solar radiation of 1120 W/m² can be recorded at ranging atmospheric temperatures from 25 °C to 37 °C and wind speeds peaking of 4 m/s. These environments offer a favourable operating condition for solar PV installation under any real field deployments. The continuous mining operations like drilling, blasting and hauling generates a significant dust deposition density over the panel surface which is considered as the unfavourable operating condition of solar PV under mechanised iron ore mines.
Map showing the geographic location of the study site where the field study was conducted. (Solar paper map was taken from Google – https://shorturl.at/c11td).
The mining industry includes heavy machinery operations, generates significant dust cloud in and around the mines that provide a challenging dynamic condition for optimizing the performance of solar PV Panel. After the blasting operation, a heavy excavator of capacity 6.5 m³ and 55 MT dumpers are used to transport the fragmented material. Two different drilling machines of 270HP and 380HP are used to create 150 mm diameter blastholes. Even though of usage of dust control measures like water injection and control drilling operations mining industry generates significant dust cloud that is sufficient to degrade the panel performance. Due to fast and dynamic dust condition this mining sites is well suited for study dust impact and its mitigation approach on solar PV panel performance. The site provides validates the effectiveness of developed automatic dust cleaning system under any harsh dusty environments. Figure 1 shows the geographic location of selected study site. From Fig. 1, the positioning of geological map within Karnataka State demonstrates the relevance of this study under the operating mining condition.
The performance of PV panel under dusty exposure is studied under real operating mining condition where no artificial or manual deposition was performed for assessing the panel performance. The purpose of this study is to assess the effeteness of developed cleaning system under real operating environment, and a site-specific cleaning system can be designed for different seasonal condition. During the study period daily measurements of weather data like temperature, humidity, and wind speed were recorded. These measurements help us to establish the link between dust deposition and environmental parameters. Though these variables cannot control but their analysis will help in developing an efficient dust cleaning system.
A twenty six week of field study is designed to investigate the dust of dust deposition on the performance of solar PV panel under operating condition of mechanized iron mines. Two identical polycrystalline solar panels kept side by side facing towards south near weighting bridge area of the selected mechanised mines. This arrangement help in comparing the panel performance of dusty and clean panel under same environmental conditions. One panel is designated as the “dusty panel,” which is left uncleaned during study period whereas other is designated as “clean panel” where daily cleaning is performed. This direct comparison between clean and dusty panel offers many insights that presents realistic dynamic challenge to operate the panel at its full potential.
The deposition of dust is measured by placing the filter paper of identical panel surface area adjacent to the clean panel. By doing the weight analysis of pre and post dust deposition in filter paper provides the daily variation of deposited dust over the panel surface that left undisturbed throughout the day. After every 24 h the filter paper removed and weighed using a high-precision (accuracy: ±0.001 g) digital weighting machine. The difference in pre and post deposition of dust mass is divided by the panel surface area which gives the deposition density in grams per square meter (g/m²). This process is repeated daily throughout the study period that enables a time-series record of dust deposition. The comprehensive time series analysis of 26-week provides a complete assessment of long-term trends of dust deposition and performance degradation under real mining conditions. Table 1 presents the weekly deposition of dust over the panel surface which is showing variations in daily accumulation due to operational and environmental factors. These variations are considered to determine the optimal cleaning frequency that indicates the point at which panel efficiency degrades if left uncleaned.
Table 1 indicates the progressive and seasonal impact of dust deposition over the panel surface from the January–June. It summarizes the weekly and total surface deposited dust densities. The data of Table 1 shows low deposition during winter months (January–February), gradually increasing during peak summer (May). From peak summer to early monsoon dust deposition again reducing that shows the lesser impact of dust in this phase. Therefore, the entire study period is divided into three different phases such as dry winter, summer and early monsoon. The trends of deposited dust densities over the panel surface confirm the need of dynamic shift in cleaning cycle due to variation in deposited dust particles. This variation also provides the alteration in the panel performance under diverse operating condition. This establishes a strong correlation between electrical output and dust deposition.
A two identical 20 W polycrystalline solar panel termed as clean and dusty used in this study is shown in Fig. 2. A weekly comparison between clean and dusty panel is used in assessing the optimum cleaning schedule for different weeks of study period. The comparison of clean and dusty panel is performed for total twenty six week of study period that enable the assessment of seasonal analysis of solar panel performance under harsh operating mining condition. The dynamic variations in operating seasons and mining activities demonstrates the need of dynamic cleaning schedule that operate at its optimum value. The technical specification of 20 W and 10 W (used in cleaning system design) solar panel is presented in Table 2. The key electrical parameters such as output power, current, and voltage were measured using a 320 Ω rheostat and two digital multimeters (one functioning as an ammeter and the other as a voltmeter). The collected electrical parameters is analysis to study the impact dust accumulation on solar panel performance. This experimental setup offered a comprehensive analysis of the performance degradation of solar panel caused by dust accumulation. This analysis provides the initial evidence to establish a correlation between dust deposition and solar panel efficiency. This preliminary understanding helps in determining the optimal cleaning frequency. This optimum cleaning subsequently supports the efficacy of the developed cleaning system for removing the dust particles form the panel surface.
Close-up view of the two identical 20 W polycrystalline solar panels used in the study.
Table 3 provides the detailed technical specifications of all measuring instruments used in this study. All instruments were pre-calibrated before field deployment as per manufacturer standards. To avoid atmospheric variability measurements were taken during clear sky conditions. The validation of developed dust cleaning system is performed on 10 W mono-crystalline PV panel and the performance of panel is recorded in post-cleaning operation under real mining dust exposure.
To mitigate the impact of dust on panel performance an automatic dry dust cleaning system is designed and implemented in real operating mining condition. This simulates the efficiency of developed dust cleaning system under harsh mining environments. The main purpose of designing this cleaning system is to minimise the need of human intervention and water consumption. This dry-cleaning system offers the best performance of installed solar panel in harsh mining environments. The field validation of developed cleaning system is performed with 10 W polycrystalline solar PV panel in peak dust deposition period. This small developed prototype allow the operational adjustments during field validation that gives a strong foundation for its larger installation area. This approach allowed a precise control on design process and facilitated adjustments as per dynamic operating condition.
The main consideration while designing the automatic cleaning system is to establish the effective coordination between mechanical and electrical components of cleaning system. This coordination is controlled by microcomputer assembly known as Arduino microcontroller. This is the main part of cleaning system which governs the entire cleaning process. This control the operation of motor driver circuit (L293D) that is direct the movements of DC gear motor. This facilitates the movements of wiper arrangements over the panel surface. The speed of wiper can be controlled by motor driver circuit that makes it more suitable to use over the panel surface under dynamic dusty condition. The wiper is freely mover across two ends of solar panel and removes the deposited dust from its surface. The wiper consists of a dry sponge material that effectively clears dust while minimizing friction over the surface that provides less damage to the glass integrity.
The dry sponge cleaning wiper provides lightweight that gives less mechanical stress on the panel glass during the cleaning operation. This help in developing an effective cleaning technique that removes significant dust from the panel surface. A 30-laboratory cleaning trial is performed over the panel surface and no surface damage is reported over the panel surface. These tests will help in defining the maintenance schedule and lifecycle analysis of the panel surface. The wiper is moved over the panel surface through the two endless belts which is positioned on either side of the panel. This belt is powered by the DC gear motor that rotate the belt that facilitate the top and bottom movement of the wiper over the panel surface. Wooden wheels support the belts and guide the wiper as it moves across the panel. When wiper is moved across the panel surface then its direction is controlled by the reversing the motor operation. This can be achieved using motor driver circuit which is connected with pin 26 and 28 of Arduino microcontroller as shown in Fig. 3. When wiper reaches at one end of the panel then it meets limit switches and activates it for providing smooth flow across the panel surface without risk of mechanical overload.
Circuit diagram of the proposed dust cleaning system.
Figure 3 presents the schematic circuit diagram of developed automatic dust cleaning system. A real the clock (RTC) triggers the Arduino microcontroller that initiate the cleaning dust system. The RTC give the activation pulse at predetermined intervals and entire cleaning system starts. Upon activation, the microcontroller sends the initiation pulse to the motor driver circuit that trigger the movement of wiper though belt rotation. The limit switches control the direction of wiper movement by sending reverse pulse to the motor driver circuit. The operational flow of this automated cleaning mechanism is further presented in Fig. 4.
The photographic view of developed dust cleaning system is shown in Fig. 5. Various operational components including the belts, motor, and wiper mechanism, are assembled onto a solar panel. The system is powered by a 12 V DC power supply that provides a stable and efficient energy source for continuous operation of cleaning system. Due to dry sponge characteristics of wiper panel dust not sticks with wiper surface that enables multiple cleaning cycles. This improves the effectiveness of developed dust cleaning system under harsh dusty condition. In the field every morning real-time clock (RTC) triggers the cleaning system for removing accumulated overnight dust from PV panel surface. The automatic cleaning system offers benefits to in remote or difficult-to-access areas where manual cleaning would be impractical.
Flowchart of the automatic dust cleaning system.
Developed dust cleaning mechanism.
The Algorithm 1 as mentioned in below section provides the complete operational logic of the developed dust cleaning system. The provided pseudocode presents the working of automatic dust cleaning system based on the constant cleaning interval and available motor logic. The pseudocode simulates cyclically nature of developed dust cleaning system that requires no manual intervention once programmed properly.
Operation logic of the automated dry-cleaning system.
The economic viability of the proposed automated cleaning system was evaluated by balancing energy yield recovery with system cost. The cleaning frequency was determined using the normalized power loss data from the field, which indicated that the highest performance degradation occurred in the first three days, followed by a more gradual decline. Cleaning every 3rd or 4th day showed to recover approximately 35–38% of lost energy, aligning with a practical cost-benefit threshold.
The cost breakdown included: Arduino microcontroller (₹500), motor driver and DC gear motor (₹700), RTC module and limit switches (₹400), sponge-based wiper and belts (₹300), and panel mounting frame (~₹500). The system operates on a 12 V DC power supply with negligible operational power draw (5–10 W/session). With total capital investment under ₹3,000 and considering average electricity rates of ₹7/kWh in India, the system pays for itself in under 6–7 months when deployed on larger PV arrays.
The long-term impact of dust deposition on solar PV performance is evaluated for a 26-week period ranging from January to June 2023. The study represents the feasibility of utilisation of solar energy in an operational mining condition. Here the focus is to optimize its performance by determining optimum cleaning cycle and validation of developed water less dust cleaning system. The main objective of this study was to capture the progressive degradation pattern under actual mining and seasonal conditions. Table 4 shows the readings obtained during the study which incorporates the values of average solar radiation, dust deposition density and electrical parameters for both clean and dusty panel. During the winter months (Weeks 1–8), dust accumulation ranged between 2.1 and 4.5 g/m², attributed to dry atmospheric conditions and moderate wind speeds (2–3 m/s). A pronounced increase occurred during the pre-summer phase (Weeks 9–17), when deposition peaked at 5.5 g/m². This time accompanied heavy mining work such as drilling, blasting, and hauling operations which is performed in dry windy weather. The early monsoon period (Weeks 18–26) exhibited less dust deposition due to rain and higher humidity, which helped clean the panel surface a bit.
During the initial phase of study in week-1 clean panel produced a maximum power output of 9.8 W when compared to 6.9 W of dusty panel. This indicates the reduction of nearly 30% in maximum output power whereas short-circuit current exhibited a sharper decline of 22.4%. The open circuit voltage shows slight reduction of 1.5%. This confirms that dust majorly affects the short circuit current and maximum power output as compared to open circuit voltage. This is mainly due to light scattering and absorption phenomena of dust deposition. Over time, this difference became more pronounced, as dust thickness increased and surface roughness enhanced light attenuation. By week-14, dust accumulation was highest. The power of the dusty panel dropped to 3.5 W. In contrast, the clean panel stayed at 9.6 W. This results in a 63.5% decrease in power generation.
A week 1 to 8 is the representation of winter months where dust accumulation ranged between 2.1 and 4.5 g/m². This attributed to dry atmospheric conditions and moderate wind speeds in the range of 2–3 m/s. During this period a progressive loss in optical transmittance was observed which reduces the electrical output of solar PV panel. During this phase, the average solar irradiance remained moderate (795–835 W/m²) allowing a consistent performance from clean solar panel ranging from 9.0 to 10.0 W. However, the dusty panel demonstrated a steady decline in maximum power (Pmax) from 6.8 W in week 1 to 5.1 W in week 8. This highlights the degradation of PV panel performance approximately 25% for these two months. This early trend confirmed that the dust layer primarily obstructed light penetration rather than altering cell junction properties.
The pre-summer phase from weeks 9 to 17 witnessed an increase amount of dust deposition ranging from 4.0 to 5.5 g/m². This increased deposition happening together with intensified mining operations under dry and windy conditions. The average solar irradiance increased moderately from 800 to 925 W/m². Even though, this phase provides higher amount of solar irradiance but panel does not perform well due to more dust deposition density in this phase. This higher dust deposition density reduces the panel performance due to the thick layering of dust over the panel surface. It shows a significant impact of dust on solar panel performance under favourable operating condition. In this phase, a maximum reduction of 63.54% for Pmax of solar panel is observed. This indicates a considerable degradation in the panel performance due to high exposure of dust. As shown from Table 4, dust accumulation reached its seasonal peak in week 14 due to the influence of peak dry season, intensified mining operations, and strong re-suspension winds. In this week, output power of dust panel dropped to 3.5 W while the clean panel maintained around 9.6 W. This results a reduction of 63.5% loss in power generation of solar PV panel as shown in Fig. 6. This is the peak in which highest reduction in solar power generation reported even due to the highest accumulation of 5.98 g/m2 dust density as shown in Fig. 7. Week 26 indicates the lowest deposition density of 2.20 g/m2 with the reduction of 29.70% in Pmax. This is mainly due to the higher solar radiation of 940 W/m2 when compared to 780 W/m2 of week 14. Further the panel surface and partial removal or redistribution of loosely bound dust particles caused by pre-monsoon humidity and mild rainfall events, which reduced the effective shading on the PV cells. During this period, the dusty panel’s Isc dropped below 0.36 A, and its Voc decreased by approximately 0.8 V relative to the clean panel. This reflects partial hindrance of photon absorption and charge carrier generation, as also supported by visual observation of fine, clay-rich particulate layers forming non-uniform coatings and inducing localized micro-hotspots.
Weekly reduction in maximum power output of dusty PV panel throughout the study.
Study week 18 to 26 presents the starting of early monsoon period and during this period dust deposition gradually reduced. This is mainly due to the occasional rainfall, higher humidity, and reduced airborne dust concentration. The average deposition density decreased from 4.35 g/m² in week 18 to 2.20 g/m² in week 26. This study duration shows the higher solar radiation correspondingly. The higher radiation week offers a slower reduction in maximum power output power, thus less frequency cleaning can be used in these seasons. This will reduce the cleaning cost and power that require to clean the dusty PV panel. The optimization of cleaning cycle can be be performed based on the dust deposition rate and this can be achieved systematically using fully automated dust cleaning system.
Weekly reduction dust deposition density on panel surface throughout the study.
Overall, the six-month performance trend demonstrates that dust accumulation causes a nonlinear but progressive decline in PV output, primarily by reducing the short-circuit current and maximum power output which can be seen from Figs. 8 and 9. The open-circuit voltage remains relatively stable throughout the study when compared to the short circuit current of the panel. This signifying that surface dust mainly influences optical transmittance rather than internal cell dynamics. The magnitude of performance loss was directly linked to dust load intensity and particle morphology, both of which varied seasonally due to changing meteorological conditions and mining operations. As shown in Fig. 8, short-circuit current exhibited a similar trend like maximum power output where the maximum reduction happened in the week 14. The short circuit current reduces from 0.67 amp (for clean panel) to 0.31 amp (for dusty panel). Dusty panel showed the highest value of 0.54 amp in week 26 whereas clean panel showed the value of 0.70 amp. The sharp early decline and partial later recovery illustrate that current output is the most sensitive electrical indicator of dust interference. Figure 9 presents the variation of open-circuit voltage (Voc) where the lowest value of 19.30 amp was observed. The variation of open circuit voltage least affected by the dust deposition as it logarithmically depended on the solar radiation. This slower decay supports prior findings by Fatima et al. (2014), which suggest that voltage is less sensitive to low-level shading but responds when coverage becomes extensive or non-uniform. Even then, minor voltage degradation contributes cumulatively to overall performance loss12. In the similar manner, the study in13 shows the dust buildup can reduce PV output by 50% in tropical areas under high exposure of dusty cloud.
This study presents a non-linear degradation pattern of solar panel performance under dynamic condition of mining industry. Initially a rapid decline then saturation at peak dust load (during 14th week), and partial recovery thereafter is noticed in the performance of PV panel. This highlights a dynamic cleaning schedule based on the seasonal variation of dust deposition density over the panel surface. These findings supports the flexible and site-specific maintenance strategies rather than fixed cleaning intervals for effective utilisation of solar PV panel in mining industry.
Weekly variation of short-circuit current for clean and dusty panels throughout the study.
Weekly variation of open-circuit voltage for clean and dusty panels throughout the study.
The finding of our study also supported by Elamim et al. (2024) where power output dropped by 20–60% in Mediterranean climates16. This change depended on the exposure period and the type of dust involved in the study. Similarly, Kazem et al. (2022) observed a 36% drop in PV output over 10 days in a desert region of Oman, primarily due to fine sand particles and dry air conditions19.
Our study found a maximum drop in output power at a mechanized iron mines when relatively compared with previous study. This happened even though the exposure times were similar or shorter. This stronger degradation is due to some special characteristic of mining industries:
High particulate density: Excavation, drilling, hauling, and blasting produce much airborne dust. This includes coarse mineral dust that quickly settles on panel surfaces.
Heavy dust adhesion: Mining dust has metallic oxides, clay fines, and silica particles. These stick more than sand or urban dust. This is due to electrostatic effects and moisture from machines.
Proximity to source: In our study, the panels were within 15 m of active haul roads and crushing zones. This closeness meant they faced constant soiling, with no natural or structural barriers to protect them.
Surface abrasion and micro-pitting: Coarse particles in mining dust contribute not only to optical shading but also to surface micro-abrasion, which subtly reduces light transmission even after cleaning.
The results show that soiling is especially severe in mechanized mining areas. This highlights the need for special strategies that provides the optimize solution for specific location.
Dust deposition plays a significant role in reducing the PV panel performance when deployed in mining environments. The study indicates a cyclic trend of performance degradation which is governed by local weather and mining activity. During the pre-summer phase (weeks 9–17), rapid performance decline was observed due to higher dust deposition (4.0–5.5 g/m²) and intense mining operations. In this period, maximum reduction of 63.54% in Pmax of the dusty panel is recorded. This shows the critical impact of dust accumulation even under moderate solar radiation conditions. As shown in Fig. 7, week number 9 to 14 presents the higher rate of dust deposition and this period panel performance decreases significantly higher than other study weeks. During this phase, approximately 60–65% reduction in panel power suggest that the panel reaches a quasi-saturation level of dust deposition where further accumulation causes marginal additional losses. Therefore, to maintain power generation above 70% efficiency, a cleaning interval of 3 to 4 days is recommended for this mining site. This implies the requirement adopting a dynamic cleaning schedule which is a site-specific constant. During this week frequent cleaning of 3 to 4 days needs to be facilitated for efficient utilisation of solar energy. However, week 21 to 26 shows a comparatively low power reduction and this week is experiencing a declining rate in reduction of maximum power. A minimum reduction of 29.50% (in week 24) in Pmax and maximum average solar radiation of 1020 W/m² (in week 21) is recorded during this phase of study. This offers a favourable operating condition for solar PV panel during this phase. Thus, cleaning frequency of 6 to 7 days is recommended for optimum utilisation of solar panels in mining environment. Here, even though week 21 offers a maximum average solar radiation but it perceived a highest reduction of 36.90% in maximum output power. This mainly results from the excessive dust deposition density during this period, which increases surface optical losses and thermal loading on the PV panel, thereby reducing photon absorption and electrical conversion efficiency despite higher irradiance. Moreover, intermittent factors such as partial natural cleaning, humidity variations, mild rainfall, and partial shading may have influenced the dust redistribution pattern rather than complete removal, leading to non-uniform soiling and localized heating, further contributing to performance degradation. Week 1 to 8 shows the increase trend of dust deposition and power reduction which indicates a moderate cleaning cycle of 6 to 7 days during initial phase (week 1 to 4) and fast cleaning with cycle of 3 to 4 days is recommended for optimum utilisation of solar PV panel.
A well maintained PV panel offers the average end of life of 20 to 25 years. Therefore, its maintenance structural stability can be maintained by providing less load (in terms of cleaning and external droppings) on its surface. The frequent cleaning operations subject the panel surface and mounting frame under cyclic mechanical stress which may harm the optical transmittance of surface glass. This approach maintains the structural reliability of the panel that help in maintaining its performance and end of life (EoL). Thus, optimizing cleaning frequency not only enhances annual energy yield but also extends the operational lifespan of PV systems in harsh mining environments.
The developed dust cleaning system was validated under actual mining field conditions to assess its operational performance and effectiveness in restoring solar panel efficiency. A crystalline PV panel of 10 W installed near the weighing bridge area of the active mining site. This is the same location where the comparative experiments between clean and dusty panels were performed. The purpose of choosing this site is to ensure the consistent environmental exposure and comparability of validated results. Three different representative validation phases such as Phase I (Winter–Early Dry), Phase II (Pre-Summer), and Phase III (Pre-Monsoon Transition) were selected from the 26-week study period. Each phase corresponds to a distinct dust deposition regime and irradiance condition. This analysis provides the validation of developed dust cleaning system under dynamic operating environments typical of mining zones. Figure 10 represents the performance comparison of the developed cleaning system across three validation phases. This shows the variation in the improvements of power generation of dusty panel, and its phase wise comparison is presented in Table 5. Table 5 indicates the comparison of Pmax for dusty and cleaned panels during the three validation phases. The improvement percentage was calculated as the ratio of the increase in power output after cleaning to the corresponding dusty condition.
Performance improvement of dusty panel across three validation phases.
During Phase I, the highest improvement of approximately 45% was achieved after cleaning of dusty panel. This outcome corresponds to a moderate dust deposition density combined with lower relative humidity. This provides a dry contact of deposited dust over the panel surface, which is smoothly clean the panel surface when compared to other two phases. Thereby this phase showed more improvements in the panel performance. In contrast, Phase II exhibited the lowest improvement of nearly 30%. This is primarily due to dense, cohesive, clay-rich particulates that adhered more strongly under higher dust deposition density. Additionally, this phases experience the higher temperatures and humidity that bind the deposited dust more strongly than other two phases. This is why in this phase comparatively less improvements in the performance of dusty panel is observed. These fine, compact dust layers increased surface roughness and reduced light transmittance, resulting in limited irradiance absorption and lower current generation, even after cleaning.
Meanwhile, Phase III, demonstrated a recovery of about 42%, attributed to partial natural cleaning effects caused by mild rainfall, higher ambient humidity, and weaker dust adhesion. During this phase, deposited dust freely removed from the panel surface that help in restoring panel performance more effectively. The consistent range of recovery percentages (30–45%) across all three validation phases underscores the robustness and adaptability of the developed cleaning mechanism under dynamic mining environments. These results also confirm that panel degradation and recovery trends are strongly governed by dust load variability and environmental dynamics. By validating the dust cleaning system the potential for long-term deployment solar PV in harsh can be achieved. This not only improve the panel performance but also provides an effective cleaning mechanism that maintain the structural integrity of solar PV panel surface.
The findings of our study is well supported by the recent published work that shows the improvement of automated dry-cleaning systems for PV panel. A study conducted by48 in 2019, used a silicone rubber brush for dry cleaning48. This study reported a weekly improvements of about 16% compared to control panel whereas our study shows the average of 40% improvements in the panel eprofrmance. Our prototype uses a rolling brush and smart motor control, this help the cleaning system in maintaining this higher improvements. Further, in49, a water-free cleaning robot was tested in China in 2022 which reports a maximum of 12% of improvements in the regular performance distributed PV settings. In cases of severe soiling, it improved performance by up to 25%49. Our system did much better than these benchmarks in tough mining conditions. It showed great cleaning power and practical automation, perfect for dry environments. Field validation shows that our low-cost, waterless robotic cleaner beats old dry-cleaning methods. It also provides scalable, autonomous maintenance for large PV deployments.
Solar PV panels perform differently in outdoor settings. Dust can build up on them, but many environmental factors also play a big role. Relative humidity has two effects. It can cause dust to stick to the PV surface. This makes it harder to clean, especially in the early morning or during fog when moisture is high. This can make the panel’s surface stickier. As a result, the dry cleaning systems used in this study may work less effectively.
Wind speed is another crucial factor. Moderate to high wind speeds can have both positive and negative effects. Strong wind gusts can dislodge loose dust particles. This may slightly improve panel performance. High wind speeds in mining areas can lift many airborne particles. This speeds up dust settling and makes cleaning more necessary. This is especially important in open-pit mines. There, surface disturbances and blasting create even more dust.
Ambient temperature also affects PV efficiency through its interaction with panel voltage output. As temperature goes up, panel efficiency usually goes down. This happens because solar cells have higher internal resistance. In our study, ambient temperatures varied from 25 °C to 37 °C. This, along with dust loading, worsened the drop in overall performance. In hot, dry mining areas, these effects are stronger. This may require combining cleaning and passive cooling solutions.
Dust buildup is key to this study. Its severity changes based on particle size, mineral makeup, and electrostatic traits. For example, fine particles from iron ore mining tend to be highly adhesive and compact under solar radiation. These properties increase both the thermal insulation and shading effect on PV modules. This highlights how important it is to study dust at each site. Doing so helps us model performance losses accurately.
Our findings offer solid proof from one environment. However, we recognize that we cannot fully control or isolate the impact of each environmental factor. Future research should use studies across different sites and seasons. It should also include real-time weather data and dust chemistry from the surface. These efforts can help create predictive models. These models can change cleaning schedules based on local conditions.
Understanding these interactions is crucial for using solar PV in industry. This is especially true in dusty and hot places, like mines. A smart cleaning plan looks at dust buildup, weather, panel position, and how dust sticks. This approach makes solar energy systems more reliable and affordable.
The study shows that automated cleaning works well for small solar PV systems in dusty mining areas. However, we must recognize some limits before applying it on a larger scale. First, the cleaning system was validated on 10 W and 20 W panels in a single iron mine located in southern India. Dust particle size, makeup, and buildup rates here differ from those in coal, bauxite, or limestone mines. Airborne particles act differently depending on certain geological and operational conditions.
The system’s design may require significant customization. This is true for the sponge wiper and motor capacity, especially with larger panels or different array setups. The best cleaning schedule found in this study may not fit all situations. Places with more dust or finer particles might need cleaning more often. On the other hand, areas with regular rain or natural dust movement may require less cleaning. So, future plans should look into real-time dust monitoring. Also, dynamic cleaning schedules based on specific thresholds are important to consider.
Economic constraints also pose a challenge. Large-scale deployment can lead to higher costs for setup and upkeep. It may also cause syncing problems between arrays and increase the risk of mechanical wear over time. These challenges necessitate cost–benefit evaluations tailored to specific mining environments. Harsh conditions, like abrasive dust and extreme temperatures, can shorten component lifespans. So, the system may need more ruggedization.
In summary, the current findings are promising. However, to scale this solution, we need adaptive designs and strategies that fit specific contexts. Future research should test the system at different mining sites. It needs to cover various geological settings and dust levels. This will help ensure the system’s reliability and cost-effectiveness in different conditions.
This study reported a significant operational and economical loss of solar panel performance due to dust accumulation. A weekly power loss of approximately 35–45% was observed due to uncleaned solar panel in mining environment. This reduction is significant when compared to power loss in residential area. To extract maximum output power PV panel needs to clean regularly but over and under cleaning can disturb the effectiveness of solar PV installation. Over cleaning of solar panel may reduce the optical properties of glass and increase the cost of the operation. Thus, there is a need to maintain a proper balance among each cleaning cycle. This study recommend a weekly cleaning for the solar panel which is installed in the iron ore surface mines which is a day operative mines having mining operations such as exaction, hauling, drilling, blasting. The developed automated, waterless cleaning system demonstrated a gain of 38.46% in the output power of cleaned panel. This confirms the practical effectiveness of the developed cleaning system in maintaining energy efficiency under harsh, dust-intensive conditions. Such improvements translate to substantial gains in energy productivity, reduced manual intervention, and enhanced sustainability in industrial-scale PV installations.
Future work will focus on integrating a predictive maintenance framework that enable intelligent scheduling that monitor real-time dust accumulate data, weather conditions, and performance feedback. A comprehensive life-cycle cost analysis (LCCA) will also be undertaken to evaluate the economic feasibility and long-term return on investment (ROI) of deploying the system across diverse industrial sites. Further, the scalability and performance will be assessed for a larger PV installations under varying climatic zones, including arid, humid, and high-altitude mining regions.
Additionally, advanced statistical analyses such as confidence interval estimation, RMSE-based trend validation, and dust-type sensitivity analysis can be performed to develop an universal cleaning model. In addition to this, a comparative assessment across different mining environments such as arid zones in Rajasthan, humid mines in Odisha, and high-altitude operations in North East part of India will be performed. These efforts would help in establishing a flexible, data-driven and smart maintenance strategy that can dynamically adapt to local environmental and operational variations. This approach will provide an effective pathway to sustainable solar energy utilization in the mining industry and other high-dust sectors.
The purpose of this study is to collectively establish a quantitative framework for sustaining PV efficiency under harsh environmental exposure. This study investigated the impact of dust on the performance of solar PV panel in an active mining environment and optimized the cleaning frequency for enhanced energy recovery. Further, the study presents an innovative dry dust automatic cleaning system which is validated in the real mining condition. A systematic 26 week field analysis revealed that dust deposition density over the panel surface varied from 2.1 to 5.9 g/m2 which is depends on the seasonal and surrounding operating conditions. The highest reduction of 63.50% and 53.57% in maximum output power (Pmax) and short circuit current of solar PV panel is recorded during the pre-summer phase. This characterized by dry weather and higher generation of dust deposition density due to intense mining activities. The pre-summer phase of weeks 9 to 17 witnessed an increase amount of dust deposition ranging from 4.0 to 5.5 g/m² in comparison to pre-monsoon where due to mild rainfall and particle cleaning reducing dust deposition density (ranging from 4.35 g/m2 to 2.20 g/m2). The optimization study revealed the dynamically adjusted cleaning frequency based on the seasonal and operational variations in the mining environment. During the weeks 9 to 17, PV panels experienced the highest dust deposition density rate of 5.98 g/m2 (in week 14) that indicates a more frequent cleaning cycle. Therefore, a cleaning interval of 3 to 4 day is recommended during this period to sustain more than 70% power efficiency. In contrast, the transition and late dry phases (weeks 21–26) exhibited comparatively lower dust loads and a minimum power loss of 29.50%. Thus, a moderate cleaning cycle of 6 to 7 day is recommended for this phase for optimal energy yield. The early winter–dry period (weeks 1–8) showed moderate deposition trends, due to this the initial cleaning frequency of 6 to 7 day is shifted to 3 to 4 days during the later phase of this period. By optimizing the cleaning cycle a less mechanical load can be maintained on the panel surface which improves its structural integrity. Thus, establishing a season-dependent and activity-responsive cleaning strategy not only enhances annual power recovery but also preserves the mechanical integrity and end-of-life reliability of PV panels.
Moreover, this study validated the developed automated dry-cleaning system under actual mining conditions using a 10 W PV panel setup. This validation across three environmental phases reports the average recovery of 40% in maximum output power of solar PV panel. This is a significant improvement for longer utilisation of solar energy in mining industry. The developed cleaning mechanism is light weight and low-friction system that ensured effective dust removal without visible surface abrasion. This confirms its suitability for prolonged use in abrasive mining environments. The study suggested the future work should be focused on integrating real-time dust sensing and AI-based decision algorithms to trigger adaptive cleaning events. Conducting long-duration durability tests to quantify mechanical wear and optical degradation of automated cleaning system may offer the sustainable utilisation of solar pV panel in harsh mining condition. The scaling of the developed cleaning system to clean multi-panel surface coupled with IoT-enabled cyber-physical system offer a robust predictive maintenance.
The datasets generated during and/or analysed during the current study are available from the corresponding author on reasonable request.
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Department of Mining Engineering, Aditya University, Surampalem, Andhra Pradesh, India
Abhishek Kumar Tripathi
Department of Mining Engineering, National Institute of Technology Karnataka, Surathkal, India
Mangalpady Aruna
Department of Mechatronics Engineering, Rajalakshmi Engineering College, Mevalurkuppam, India
E. Prakash
Department of Mechanical Engineering, Wollo University, Dessie, Ethiopia
S. Prabhakar
Faculty of Psychology, Shinawatra University, Bangkok, Thailand
Zhang Zhen
Department of Mechanical Engineering, Aditya University, Surampalem, India
P. V. Elumalai
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Correspondence to S. Prabhakar.
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Tripathi, A.K., Aruna, M., Prakash, E. et al. Enhancing solar PV efficiency in mining operations through optimized cleaning intervals and automated dust mitigation. Sci Rep 16, 8718 (2026). https://doi.org/10.1038/s41598-026-42709-3
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