Optimization of Photovoltaic System and Algorithm Development

This paper presents the optimization of photovoltaic (PV) systems and development of optimization algorithms for the power output of a solar PV system. The aim of the study was to investigate and understand the various existing optimization techniques and methods, then develop an algorithm that can optimize a solar PV system and compare the results. The optimization method used was MPPT (maximum power point tracking) and (Perturbation and observation) P&O algorithm. The (Instantaneous and Incremental conductance) INC algorithm and Genetic algorithm were developed. Development and simulation of the optimization methods and developed algorithms was achieved with the use of Matlab Simulink software. For this study, the output of the optimized system with the MPPT method trained with P&O optimization, INC algorithm and Genetic algorithm were compared with the output of an unoptimized system under different atmospheric conditions and then to each other. The results of the optimized system were compared with the result of the unoptimized system. From the result, it was found out that the optimized system has a better response, lesser error, better accuracy and tracking speed than the unoptimized system. The study revealed the need of optimization in PV system and the step-by-step process of developing an optimization algorithm was shown

Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2024-09-16
DOI
https://doi.org/10.5281/zenodo.13769832
Primary Topic
Protein purification and stability
Type
article
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article

Optimization of Photovoltaic System and Algorithm Development

Zenodo (CERN European Organization for Nuclear Research)
Protein purification and stability
article

Optimization of Photovoltaic System and Algorithm Development

article en

Abstract

This paper presents the optimization of photovoltaic (PV) systems and development of optimization algorithms for the power output of a solar PV system. The aim of the study was to investigate and understand the various existing optimization techniques and methods, then develop an algorithm that can optimize a solar PV system and compare the results. The optimization method used was MPPT (maximum power point tracking) and (Perturbation and observation) P&O algorithm. The (Instantaneous and Incremental conductance) INC algorithm and Genetic algorithm were developed. Development and simulation of the optimization methods and developed algorithms was achieved with the use of Matlab Simulink software. For this study, the output of the optimized system with the MPPT method trained with P&O optimization, INC algorithm and Genetic algorithm were compared with the output of an unoptimized system under different atmospheric conditions and then to each other. The results of the optimized system were compared with the result of the unoptimized system. From the result, it was found out that the optimized system has a better response, lesser error, better accuracy and tracking speed than the unoptimized system. The study revealed the need of optimization in PV system and the step-by-step process of developing an optimization algorithm was shown

Zenodo (CERN European Organization for Nuclear Research)
Affordable and clean energy
Openalex Percentile: Top 65%
Protein purification and stability
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Optimization of Photovoltaic System and Algorithm Development · Zenodo (CERN European Organization for Nuclear Research) (2024) | TGRS Research Map | TGRS