Statistical approach for the optimum selection of photovoltaic modules on a specific site Available to Purchase

This paper introduces a probabilistic approach (PA) for the optimum selection of various photovoltaic (PV) modules manufactured by different suppliers to select the most suited module at a specific site location. This approach is based on fitting the probability distributions of the irradiance data measured at a specific hour of a typical day over a long term period (7 years). The goodness of fit test is employed to determine the best fitted probability density function which is then used in the calculation of the average output power and capacity factor (CF) of each module. Thus, the module with the highest average CF over the year is therefore considered as the best suited module for the given site location. The source files of solar irradiance database are approved by the Egyptian Meteorological Authority. Detailed modeling of the PV system characteristics using MATLAB/Simulink has been introduced, which shows complete stepping procedures and respective results. The combination of the detailed PV modeling along with the PA facilitates precise prediction of the best module in terms of output power under varying operating conditions and partial shading for the specified site.