Global Maximum Power Point Tracking of Solar Photovoltaic Strings under Partial Shading Conditions Using Cat Swarm Optimization Technique

T Nagadurga,V S Vakula,P V R L Narasimham

doi:10.3390/su131911106

T Nagadurga, V S Vakula + Show 1 more

Open Access

https://doi.org/10.3390/su131911106

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Abstract

The power versus voltage curves of solar photovoltaic panels form several peaks under fractional (partial) shading conditions. Traditional maximum output power tracking (MPPT) techniques fail to achieve global peak power at the output terminals. The proposed Cat Swarm Optimization (CSO) method intends to apply MPPT techniques to extract the global maxima from the shaded photovoltaic systems. CSO is a robust and powerful metaheuristic swarm-based optimization technique that has received very positive feedback since its emergence. It has been used to solve a variety of optimization issues, and several variations have been developed. The CSO-based maximum power tracking technique can successfully tackle two major issues of the PV system during shading conditions, including random oscillations caused by conventional tracking techniques and power loss. The proposed techniques have been extensively used in comparison to conventional algorithms like the Perturb and the Observe (P and O) technique. The main objective is to achieve a tracking speed for extracting the Maximum Power Point (MPP) from the solar Photovoltaic (PV) system under fractional shading conditions by using CSO. Modeling of the solar photovoltaic array in the MATLAB/Simulink platform comprises a photovoltaic module, a switching converter (Boost Converter), and the load. The PSO and CSO techniques are applied to the PV module under different weather conditions. The PSO algorithm is compared to the CSO algorithm according to simulation results, revealing that the CSO algorithm can provide better accuracy and a faster tracking speed.

Highlights

Fossil-fuel-based power plants cause irreparable damage to the environment by releasing pollutants into the atmosphere, though their primary task is to generate electrical energy
The KC200GT (Kyocera, Gurugram, India) solar module was used for modeling the PV string to achieve10a of broad understanding of the partial shading conditions of the solar photovoltaic system
This study has found that the optimization of partially shaded modules on PV strings that have a single global maximum power point (GMPP) and many LMPPs on the power versus voltage curve, can be achieved using a heuristic optimization technique called Cat Swarm Optimization (CSO)

Summary

Introduction

Fossil-fuel-based power plants cause irreparable damage to the environment by releasing pollutants into the atmosphere, though their primary task is to generate electrical energy. In this regard, solar photovoltaic systems have come to be recognized as the most suitable substitute for conventional energy sources that can sustainably generate energy. Zhu et al [2] reviewed the important morphological characteristics of an organic solar cell in their study. They obtained useful information regarding morphology optimization of NFA related OSCs, which can assist in solving the Sustainability 2021, 13, 11106.

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