1,721,020 research outputs found
Photovoltaic cleaning optimization through the analysis of historical time series of environmental parameters
Full text linkThis work investigates the possibility of using historical environmental parameter data to predict the typical soiling loss profile and the most convenient cleaning schedule for a PV site. The three-year performance of a 1 MW system in Southern Spain is evaluated using different soiling extraction methods. When the rainfall pattern is used to detect natural cleaning events, the best results are obtained if a 1.0 mm/hour threshold is considered. However, despite the optimization, setting a fixed threshold is found to lead occasionally to the over- or under-detection of cleaning events. Similar trends in the modelling results are found if the thresholds are set using the maximum hourly or the cumulative daily rainfall data, but the errors and the optimal values change depending on the rainfall dataset. The study also shows that a soiling extraction method based only on precipitation and particulate matter, calibrated against one year of PV data, is able to generate a soiling profile with a mean absolute error of 0.022 and to recommend a cleaning day within a week of the actual optimal dates. This will make it possible to estimate the soiling losses and the optimal cleaning schedule for a PV site even if no power data are available
Tracking soiling losses and cleaning profits trends
No full textSoiling 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
Spectral nature of soiling and its impact on multi-junction based concentrator systems
No full textSoiling, which consists of dust, dirt and particles accumulated on the surface of conventional or concentrator photovoltaic modules, absorbs, scatters, and reflects part of the incoming sunlight. Therefore, it reduces the amount of energy converted by the semiconductor solar cells. This work focuses on the effect of soiling on the spectral performance of multi-junction (MJ) cells, widely used in concentrator photovoltaic (CPV) applications. Novel indexes, useful to quantify the spectral impact of soiling are introduced, and their meanings are discussed. The results of a one-year experimental investigation conducted in Spain are presented and are used to discuss how soiling impacts each of the subcells of a MJ cell, as well as the cell current-matching. Results show that soiling affects the current balance among the junctions, i.e. the transmittance losses have found to be around 4% higher in the top than in the middle subcell. The spectral nature of soiling has demonstrated to increase the annual spectral losses of around 2%. Ideal conditions for the mitigation of soiling are also discussed and found to be in blue-rich environments, where the higher light intensity at the shorter wavelengths can limit the impact of soiling on the overall production of the CPV system
Comparative analysis of methods to extract soiling losses. assessment with experimental measurements
No full textThe impact of soiling on the energy yield of PV systems has recently become a major concern for PV owners, as soiling losses have reduced significantly the revenues of several PV sites. However, a large number of PV plants still lack the equipment to monitor these losses. An appropriate knowledge of soiling losses in PV modules can significantly increase the economic profits, even if possible without any specific soiling monitoring system. In this study, a first comparison of different analytical methods to extract losses due to soiling from PV performance data, without the need for specific soiling sensors, is presented. The study is based on outdoor PV power, irradiance and module temperature measurements. The experimental campaign is conducted in a low-moderate soiling location. The first results show that two of the methods assessed in this work can estimate soiling trends with a relative high accuracy, thus allowing planning adequate cleaning schedules
Monitoring photovoltaic soiling: assessment, challenges, and perspectives of current and potential strategies
Full text linkApplied sciences; energy engineering; engineering; industrial engineering; materials application; optical material
Indoor validation of a multiwavelength measurement approach to estimate soiling losses in photovoltaic modules
Full text linkSoiling is a factor that impacts the performance of photovoltaic (PV) modules. Nowadays, the research related to PV soiling monitoring is focused on optical sensors, which estimate the soiling loss through a monochromatic transmittance or reflectance measurement. However, these typically neglect the spectral profile of soiling transmittance, which tends to absorb shorter wavelengths more than the longer ones. This leads to a spectral red shift of the light that is transmitted to the PV cells of a module. Therefore, if the spectral component of soiling is not considered, the estimated soiling losses are not fully representative of those occurring in the real PV modules. This investigation aims to address this issue by modeling the full soiling transmittance spectrum using several monochromatic light sources in a new version of a previously presented optical soiling sensor, called “DUSST”. Four different combinations of mono-wavelength light-emitting diodes have been used to model the full spectral transmittance profile of artificially soiled PV glass coupons and to estimate the electrical losses of distinct PV technologies. The results show that the errors in soiling estimation can be minimized by using an appropriate wavelength combination. The difference between the measured and the estimated soiling losses can be lower than 3% if the most convenient wavelength combination is utilized. In the case of m-Si, which is the prevalent PV technology nowadays, the application of the optimum wavelength combination is found to reduce the maximum measurement error to 2.6%, from the initial 7.7% returned when a single wavelength was employed
Extracting and generating PV soiling profiles for analysis, forecasting, and cleaning optimization
Full text linkThe identification and prediction of the daily soiling profiles of a photovoltaic site is essential to plan the optimal cleaning schedule. In this article, we analyze and propose various methods to extract and generate photovoltaic soiling profiles, in order to improve the analysis and the forecast of the losses. New soiling rate extraction methods are proposed to reflect the seasonal variability of the soiling rates and, for this reason, are found to identify the most convenient cleaning day with the highest accuracy for the investigated sites. Also, we present an approach that could be used to predict future soiling losses through the implementation of stochastic weather generation algorithms whose ability to identify in advance the best cleaning schedule is also successfully tested. The methods presented in this article can optimize the operation and maintenance schedule and could make it possible, in the future, to predict soiling losses through analysis based only on environmental parameters, such as rainfall and particulate matter, without the need of long-term soiling data
Comparison of methods for estimating the solar cell temperature and their influence in the calculation of the electrical parameters in a HCPV module
Full text linkThe electrical parameters of a multi-junction solar cell are influenced by its operating temperature. Hence, the estimation of the cell temperature of a HCPV module is critical for its electrical characterization. However, measuring the cell temperature of a HCPV module is a complex task due to its unique features. This paper calculates the cell temperature in a HCPV module by using a number of methods to address this important issue. We conducted a comparative study of three methods used to estimate the cell temperature of a HCPV module: the Voc-Isc method, the thermal resistance method and the lineal method. The results show that all of the studied methods can be used to estimate cell temperatures with an acceptable margin of error
Economics of seasonal photovoltaic soiling and cleaning optimization scenarios
Full text linkThe 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
Optical degradation impact on the spectral performance of photovoltaic technology
Full text linkThe exponential growth of global capacity along with a reduction in manufacturing costs in the last two decades has caused photovoltaic (PV) energy technology to reach a high maturity level. As a consequence, currently, researchers from all over the world are making great efforts to analyse how different types of degradation impact this technology. This study provides a detailed review of the impact of different optical degradation mechanisms, which mainly affect the transmittance of the top-sheet encapsulant, on the spectral response of the PV modules. The impact on the spectral performance of PV modules is evaluated by considering the variations of the short-circuit current since this is the most widely used parameter to study the spectral impact in outdoors. Some of the most common types of optical degradation affecting the performance of PV modules worldwide, such as discoloration, delamination, aging and soiling have been addressed. Due to the widely documented impact of soiling on the spectral response of modules, this mechanism has been specially highlighted in this study. On the other hand, most of the publications analysed in this review report optical degradation in PV modules with polymeric encapsulant materials. Furthermore, an innovative procedure to quantify the spectral impact of degradation on PV devices is presented. This has been used to analyse the impact of two particular cases of degradation due to soiling and discoloration on the spectral response of different PV technologies
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