APPLICATION OF THE MAXIMUM POWER POINT TRACKING CONTROL ALGORITHM BASED ON PARTICLE SWARM OPTIMIZATION FOR A PHOTOVOLTAIC TREE IN REAL TIME

Abstract

The energy conversion efficiency of photovoltaic cells has always been a focal point in solar power generation systems. In the endeavor to enhance efficiency,
monitoring and optimizing the Maximum Power Point Tracking (MPPT) is considered an effective approach. This study designs a MPPT controller utilizing the
Particle Swarm Optimization (PSO) algorithm to maximize power extraction from PV modules. The proposed technique is grounded on intelligent algorithms to
regulate the output power from PV modules and optimize the DC-DC power converter for achieving maximum efficiency. The results indicate a significant
reduction in power oscillations at stable states, which could enhance photovoltaic conversion efficiency. Irradiance intensity is also varied to assess the
effectiveness of PSO algorithm in seeking the maximum power point. The research results demonstrate that the PSO algorithm can identify the maximum power
point with good convergence speed under varying irradiance conditions.