• Energy Research

The natural soiling of photovoltaic cover glass has recently been shown to include both an inorganic and organic particulate matter. Under favorable growth conditions, the latter can lead to the growth of dense colonies of filamentous fungi, which potentially leads to measurable performance losses over time. Herein, we report on a field study where glass coupon samples were deployed in soiling-prone locations, which focused on Dubai (United Arab Emirates) and Mumbai (India). For each site location, clear differences in the soiling were observed. The samples from Mumbai were contaminated with an abundance of filamentous fungi, whereas the samples from Dubai had primarily inorganic contamination. The effectiveness of soiling mitigation strategies, which include cleaning techniques and glass coatings, are discussed in detail.

AbstractOne hundred and two environmental and meteorological parameters have been investigated and compared with the performance of 20 soiling stations installed in the USA, in order to determine their ability to predict the soiling losses occurring on PV systems. The results of this investigation showed that the annual average of the daily mean particulate matter values recorded by monitoring stations deployed near the PV systems are the best soiling predictors, with coefficients of determination (R2) as high as 0.82. The precipitation pattern was also found to be relevant: among the different meteorological parameters, the average length of dry periods had the best correlation with the soiling ratio. A preliminary investigation of two‐variable regressions was attempted and resulted in an adjusted R2 of 0.90 when a combination of PM2.5 and a binary classification for the average length of the dry period was introduced. Copyright © 2017 John Wiley & Sons, Ltd.

The accumulation of soiling on photovoltaic modules and on the mirrors of concentrating solar power systems causes non-negligible energy losses with economic consequences. These challenges can be mitigated, or even prevented, through appropriate actions if the magnitude of soiling is known. Particle counting analysis is a common procedure to characterize soiling, as it can be easily performed on micrographs of glass coupons or solar devices that have been exposed to the environment. Particle counting does not, however, yield invariant results across institutions. The particle size distribution analysis is affected by the operator of the image analysis software and the methodology utilized. The results of a round-robin study are presented in this work to explore and elucidate the uncertainty related to particle counting and its effect on the characterization of the soiling of glass surfaces used in solar energy conversion systems. An international group of soiling experts analysed the same 8 micrographs using the same open-source ImageJ software package. The variation in the particle analyses results were investigated to identify specimen characteristics with the lowest coefficient of variation (CV) and the least uncertainty among the various operators. The mean particle diameter showed the lowest CV among the investigated characteristics, whereas the number of particles exhibited the largest CV. Additional parameters, such as the fractional area coverage by particles and parameters related to the distribution's shape yielded intermediate CV values. These results can provide insights on the magnitude inter-lab variability and uncertainty for optical and microscope-based soiling monitoring and characterization.

Soiling losses can be mitigated by cleaning the PV modules. However, the profitability of PV cleaning varies with time, influenced by the electricity price, the module efficiency and the cleaning costs. The present work analyzes the trends in soiling losses and soiling mitigation profitability for the continental U.S. The initial results show that, because of the lowering electricity price, the portion of PV capacity economically worth cleaning is decreasing. This means that, even if the economic impact of soiling is lowering, the fraction of energy yield lost due to soiling is actually increasing, because of the reducing mitigation activities.

<b>Accepted Manuscript (Postprint): </b>L. Micheli et al., “Improved PV Soiling Extraction through the Detection of Cleanings and Change Points,” IEEE Journal of Photovoltaics, Volume: 11, Issue: 2, March 2021.

Abstract The present study analyzes the soiling losses of a 1 MW photovoltaic system installed in the South of Spain. Both the Levelized Cost of Energy and the Net Present Value are used to compare the convenience of different mitigation strategies. It is found that also photovoltaic installations located in moderate regions, where the yearly soiling losses are limited to 3%, can suffer of a severe seasonal soiling, with power drops higher than 20%. In these conditions, an optimized cleaning schedule can be considerably beneficial from an economic perspective. For the given site, an optimal cleaning schedule generates a raise in profits up to 3.6% if one yearly cleaning is performed within a ±31-day window in summer. The convenience of one and multiple cleaning strategies is investigated by considering variable electricity prices and cleaning costs. In addition, the impact of the module efficiency on the cleaning strategy is analyzed. It is found that an optimized cleaning schedule can enhance the benefits of installing high efficiency modules, as it increases the amount of energy recovered through each cleaning and, therefore, the profits.

AbstractThe present paper evaluates the soiling losses of a 3.25‐MW photovoltaic (PV) system installed in central Chile, 200 km north of Santiago, and analyzes the nonuniform soiling deposition between the various strings for a period of 3 years. A robust methodology is developed to extract, in the most systematic way, 142 reliable soiling profiles from the 256 PV power time series recorded on site. It is found that, if unmitigated, soiling would reduce the annual DC energy generation by 8%, with a factor of 2× between the losses of the most and least affected strings. Most of the losses are registered on the edges of the plant, closer to traffic and unpaved roads. The most soiling intense months are in summer, result of the infrequent rainfalls and of the high concentrations of suspended particles that characterize this season. The revenues and the costs of different manual cleaning frequencies are evaluated and compared to identify the optimal soiling mitigation strategy for this site. Three cleanings per year are found to return the highest profits for the economic conditions considered in this study. However, a sensitivity analysis shows how different cleaning costs and electricity prices would affect the soiling mitigation strategy. In addition, in light of the nonuniform soiling deposition distribution, the possibility of cleaning only selected strings rather than the full PV plant is discussed.