Estimation of fundamental circuit parameters affecting maximum power transfer in a typical photovoltaic panel using the hybrid genetic algorithms

As the evolving technology and growing energy demand are increasing, reserve energy sources are rapidly declining. This situation has increased the interest in alternative energy sources and has made renewable energy sources important due to their energy potential and continuity As find some alternative energy sources as developing the owned sources for increasing yields is important too. For this reason, in this study photovoltaic (PV) systems were discussed and estimated fundamental circuit parameters affecting maximum power transfer in a typical photovoltaic panel using the genetic algorithms. PV systems which provide electrical energy from solar energy systems has been defined with electrical circuits. The literature survey has shown that there are few circuit models to obtain a better understanding of the PV cell characteristic. The most known approximate circuit models of the PV cell is described by the single diode model which used in this study. In order to transfer maximum power from a PV cell, it is important to estimate the certain parameters within acceptable error range. However, manufacturer data sheet of PV panels are not give information about diode ideality factor n, series resistnace R_s and shunt resistance R_p. Firstly, for understanding the effect of this three unknown parameters on the PV characteristic curves, the PV system was sımulated and the characteristic curves of system was plotted by MATLAB/SIMULINK package program. Single diode model involves in a transcendental equation which may have some difficulties directly to calculate the load current or the output voltage. Therefore the Lambert W function is used to reformulate voltage-current or current-voltage characteristic equation for easy computation. Thus, the load current or the output voltage can easily be calculated by the corresponding characteristic equation depending on known values of the circuit parameters. After that the resulting equations were used with manufacturer data sheet parameter values and the unknown parameters was estimated for amounts of different temperature and irradiance by genetic algorithms.