PV maximum power-point tracking using modified particle swarm optimization under partial shading conditions

Al-Wesabi Ibrahim,Tariq Almoqri,Zhijian Fang,Mohammad Abu Sarhan,Ahmed G Alareqi,Min Ding,Ayman M Al-Rassas,M.B Shafik

doi:10.23919/cjee.2020.000035

Abstract

PV maximum power-point tracking using modified particle swarm optimization under partial shading conditions

Highlights

A novel maximum power-point tracking approach is proposed based on studies investigating the output characteristics of photovoltaic (PV) systems under partial shading conditions
If a PV system operates under a partial shading condition (PSC), the power-voltage (P-V) characteristic curve of the PV system will have different local maximum points resulting from the connection of bypass diodes to reduce the impact of hot-spots
The key purpose of this study is to propose an intelligent maximum power-point tracking (MPPT) tracker that enables the efficient prediction of the global maximum power-point (GMPP) from a PV system, regardless of the condition of the surrounding atmosphere, whether under uniform or non-uniform solar irradiation levels

Summary

Introduction

A novel maximum power-point tracking approach is proposed based on studies investigating the output characteristics of photovoltaic (PV) systems under partial shading conditions. Optimization under Partial Shading Conditions point under these conditions, and there is a need to propose a more suitable control system that can distinguish between local and global maxima to ensure the maximum possible power, enhancing the total system efficiency. For this reason, the key purpose of this study is to propose an intelligent maximum power-point tracking (MPPT) tracker that enables the efficient prediction of the global maximum power-point (GMPP) from a PV system, regardless of the condition of the surrounding atmosphere, whether under uniform or non-uniform solar irradiation levels

Objectives

Methods

Conclusion