DESIGN OF MAXIMUM POWER POINT TRACKING (MPPT) CONTROLLER BASED ON PARTICLE SWARM OPTIMIZATION ALGORITHM FOR PHOTOVOLTAIC SYSTEM IN PARTIAL SHADING CONDITION (PSC)

Abstract

Fossil energy still dominates the energy supply, even though fossil energy is non-renewable energy whose supply is decreasing yearly. Fossil energy has a bad impact on the environment, especially on global warming. The use of renewable energy sources for power generation is increased, such as solar photovoltaic systems that convert solar radiation into electrical energy. Non-linear changes in solar radiation intensity (insolation) and panel surface temperature are the main problems of photovoltaic systems for effective energy conversion. Besides temperature and insolation, partial shading condition (PSC) also greatly influences solar cells' characteristics. This partial shading condition (PSC) causes the output characteristics of the PV module to become more complex and shows several peaks in its characteristic curve. The controller is needed to keep photovoltaic operating at its highest maximum power point in partial shading conditions. In this paper, the Maximum Power Point Tracker (MPPT) method with particle swarm optimization (PSO) algorithm is used to maximize power output to be at the maximum area (Maximum Power Point). The parameters of the PSO algorithm will be set in such a way that it can reach the MPP point in a relatively short time. This paper depicts that the PSO algorithm can maintain power at 14.4 W at 0.6 seconds under partial shading conditions. Therefore, the PSO algorithm is the right solution to track the optimal operating power point under partial shading conditions.
Keywords: Renewable Energy Source (RES),  Solar Photovoltaic Systems, Partial Shading Condition (PSC), Maximum Power Point Tracker (MPPT), Particle Swarm Optimization (PSO)