Novel Particle Swarm Optimization Algorithm Based on President Election: Applied to a Renewable Hybrid Power System Controller

Particle swarm optimization has been a popular and common met heuristic algorithm from its genesis time. However, some problems such as premature convergence, weak exploration ability great number of iterations have accompanied with the nature this algorithm. Therefore, in paper we proposed novel classification for particles to organize them different way. This new method which is inspired president election called President Election Swarm Optimization (PEPSO). trying choose useful omit functionless ones at initial steps besides considering effects all generated get directed fast convergence. Some preparations are also done escape To validate applicability our PEPSO, it compared other including GAPSO, Logistic PSO, Tent PSO estimate parameters controller hybrid power system. Results verify that PEPSO better reaction worst conditions finding controller.