Design of maximum power point tracking (MPPT) on two axes solar tracker based on particle swarm fuzzy

Abstract

The renewable energy currently becomes a research topic that is constantly being improved. Efforts to find alternative energy sources as a substitute for fossil fuels still continue to be discussed. Indonesia is geographically located on the equator has a big potential for solar energy. It can't be utilized optimally because still constrained conversion of PV modules that still relatively low. One of the solutions offered is to fit up solar panels with solar tracking system and Maximum Power Point Tracking (MPPT) algorithm. The method of solar tracking system seeks PV panels always perpendicular to the direction of sunlight, whereas MPPT serves to trace the maximum power PV may produce in various climatic conditions. In this study, MPPT-based Fuzzy-Particle Swarm Optimization (PSO) which integrates with fixed and tracking PV panel system to increase PV module power conversion. PSO plays a role in the search for the best fuzzy membership function parameters designed based on the defined objective function that is Mean Square Error (MSE). The result shows that MPPT Fuzzy-PSO solar tracker can increase the power output from PV by 28.84% for 10 hours of operation compared with MPPT Fuzzy-PSO fixed system.