Optimized-fuzzy MPPT controller using GA for stand-alone photovoltaic water pumping system

This paper presents a comparative study among different Maximum Power Point Trackers for Photovoltaic Water Pumping load. Comprehensive analysis and simulation of KC-120-1 PV module (source), Kyocera SD 12-30 solar pump (load) and storage tank (storage) were conducted. Multi-objective optimization based on Genetic Algorithms were performed for two MPPT techniques: perturb and observe (P&O) and fuzzy technique. A GA cost function is developed and explained for optimization purposes. The fitness function considers the irradiance variations of two climates condition (sunny and cloudy days), however the algorithm can be easily changed for considering more cases. A comparative analysis of both techniques was perform before and after optimization based on the system energy error and the water flow rate. It is demonstrated that GA-optimized Fuzzy algorithm presents a more appropriate behavior under the different climatic conditions.