Design Optimization of Photovoltaic System for Domestic Customers

Abstract

In the present work, a comparison between different population based optimization methods are applied to design optimization of standalone Photovoltaic (SPV) system. The purpose of these methodologies is to obtain optimum values of the design parameters of SPV system, such that the overall economic profit is maximized throughout the PV system lifetime operational period. Out of many design parameters available for SPV system, in the present work only few parameters are taken. The optimal design parameters chosen here are PV modules optimum tilt angle, optimum number of PV module and optimal positioning of PV modules within the provided installation area. The objective function of the proposed evolutionary optimization algorithms implemented for design optimization of the SPV system is the total profit incurred during the lifetime operational period of SPV system, which has to be maximized. Simulation results of design optimization of SPV system by using Genetic Algorithm (GA),qParticle Swarm Optimization (PSO)qand Differential Evolutionq (DE) technique are obtained. Simulation results shows that DE and PSO have similar performance and both of them had performed better compared to GA when all algorithms are computed for equal iterations and population size.