Modelling of a PV array and short time prediction of solar insolation

Abstract

The thesis describes firstly PV array modeling and simulation using a two diode model. It is necessary to represent the dynamic characteristics of a PV cell through a two diode model. From the simulation studies pursued in the thesis it is envisaged that the two diode model representation of a PV array provides improved accuracy even at low solar irradiation levels. When compared with a single diode model representation, the two diode model described in the thesis gives improved representation of the PV array. In a single diode representation, the input parameters of the PV cell were approximately with seven parameters namely IPV, Io1,Io2, Rp, Rs,a1,a2 ; but in this thesis the number of inputs have been reduced to four as it has been assumed that IO1 = IO2 while the values of a1 a2are chosen arbitrarily from [5].The reason behind going for this model is that the input parameters have been reduced so as to reduce the computational time. The accuracy of the proposed two diode model is verified by applying it to a monocrystalline Kyocera PV cell obtained from the datasheet [4] described in Table1.Further the two diode model is useful to find the I-V and P-V curves in standard test condition since it is fast, simple and accurate as well as it leads to showcase P-V and I-V curves in large array simulation and in partial shading condition. Subsequently, the thesis describes an algorithm to predict solar irradiation as the solar insolation is intermittent in nature. Hence this work considers development of an artificial wavelet neural network to determine solar insolation.