Maximum Energy Extraction in Partially Shaded PV Systems Using Skewed Genetic Algorithm: Computer Simulations, Experimentation and Evaluation on a 30 kW PV Power Plant

Abstract

This paper presents an improved Genetic algorithm (GA) for Maximum Power Point Tracking (MPPT) in shaded Photovoltaic (PV) power generation systems. The proposed GA uses shrinking population wherein fitter chromosomes are retained for next generations while lesser-performing chromosomes are removed from the population sequentially. This methodology reduces convergence time while retains major advantages of GA. The method is explained lucidly and then computer simulations and experimental results on a prototype fabricated in the laboratory are presented. The practical feasibility of the new method is then showcased by applying the new theory on a 30-kW Photovoltaic (PV) power plant established in an educational institution premise. The PV plant undergoes partial shading conditions (PSC) during morning and afternoon hours due to branches of tall trees grown around the school building. The MPPT algorithm employed in the PV plant is Perturb and Observe (P&O) which fails to track global power peak at several shading conditions leading to loss of energy. The realistic shading patterns occurring on the PV plant were recorded and the new method is shown to exhibit enhanced energy yield.