The deposition of dust, soil, and microfibers resulting from the surroundings, as well as the growth of minute pollens like moss and fungi, contributes toward photovoltaic (PV) module soiling. Soiling is a widely recognized factor that significantly reduces the power production by acting as a barrier for effective light absorption by the module. The estimated loss in the irradiance and power can be determined with the help of a soiling ratio (SR) parameter, which is the ratio of the short-circuit current (Isc) or the maximum power produced (Pmax) by a soiled module to a clean one. The measured SR is normally not constant throughout a day but changes with the position of the Sun and the amount of dust on the module. This paper proposes an empirical equation to determine the SR at any instant of time of the day based on the Sun's angle of incidence on the module and a single SR value measured at the mid of the day. First, an indoor experiment was done to examine the angular loss dependence of two totally different dust colors for the same SR at normal light incidence. Next, in an outdoor experiment, the SR of an artificially soiled module was measured over the course of the day for three conditions of high, medium, and low daily average irradiance due to variation in cloudiness. Then, an empirical equation is introduced based on an incident angle modifier for soiled and cleaned PV modules. The proposed equation was further used to determine the SR. Finally, the average residuals between the measured and the modeled SRs were determined with the help of root-mean-square deviation. The results showed that the modeled SR was determined with a deviation of ±0.21% and ±0.28%, respectively, for high-and medium-irradiance days, whereas the deviation increased to ±1.04% in the case of low irradiance due to clouds.@en

We report on an advanced modelling approach to accurately predict the energy yield of custom environment / urban integrated photovoltaic systems (E/UIPV). Several submodels are here presented, and their mutual interaction discussed. The flexibility of our software platform allows to exhaustively simulate custom horizons in combination with rigid/flexible PV modules and in presence of albedo component. In this respect, a modelling example predicts AC-side yield with <1% error on annual basis with respect to actual data. In addition, our platform can also deal with colored/bifacial modules and soiling losses for PV energy yield potential or performance prediction.@en

We report on an advanced modelling approach to accurately predict the energy yield of custom environment / urban integrated photovoltaic systems (E/UIPV). Several submodels are here presented, and their mutual interaction discussed. The flexibility of our software platform allows to exhaustively simulate custom horizons in combination with rigid/flexible PV modules and in presence of albedo component. In this respect, a modelling example predicts AC-side yield with <1% error on annual basis with respect to actual data. In addition, our platform can also deal with colored/bifacial modules and soiling losses for PV energy yield potential or performance prediction.@en

We report on an advanced modelling approach to accurately predict the energy yield of custom environment / urban integrated photovoltaic systems (E/UIPV). Several submodels are here presented, and their mutual interaction discussed. The flexibility of our software platform allows to exhaustively simulate custom horizons in combination with rigid/flexible PV modules and in presence of albedo component. In this respect, a modelling example predicts AC-side yield with <1% error on annual basis with respect to actual data. In addition, our platform can also deal with colored/bifacial modules and soiling losses for PV energy yield potential or performance prediction.@en