Evolutionary Algorithms based AGA and BPSO Computing for Hybrid Renewable Energy System

Abstract

Solar and wind Renewable system have more advantages compared to Conventional energy sources and it is environment friendly and also from economic point of view...For overcoming the problems of Conventional Energy sources, this paper proposed an hybrid renewable energy system using Different evolutionary algorithm approaches. This proposed method hybrids the three systems namely, solar PV, wind and Fuel Cell which have the biggest potential to provide power. The battery and loads are also integrated with this hybrid system. Then, the charging and discharging of this system is controlled by an Optimized PID controller for balancing the generated power and load power. Here, the PID controller works based on the rules to provide an efficient system. Also, the tuning parameters of the PID controller are enhanced by Adaptive Genetic Algorithm and Particle Swarm Optimization. Finally, the performance of the Combined Solar and wind system is tunedwith the Evolutionary algorithm based PID controller and is compared with the existing hybrid renewable systems based on Generated Power, Load side Power, Speed Controller and Torque.