Performance Enhancement of Photovoltaic System Using Nature Inspired Optimization Algorithms

Document Type : Review Article

Authors
Blessy Abdul Rahiman 1
Jayakumar Jayaraj 1
Meenal Rajasekaran 2
1 Department of Electrical and Electronics Engineering, Karunya Institute of Technology and Sciences, Coimbatore, India
2 Department of Electrical and Electronics Engineering, SRM TRP Engineering College, Trichy - 621105.
10.22059/jser.2025.391680.1540
Abstract
In recent times, consumption of non-renewable energy sources has been growing, because of the rise in population. The persistent exploitation of the conventional energy sources like fossil fuels, etc. led to insufficiency in the energy sources.Thus, the researchers detected an extra energy sourcenamed Renewable Energy Source, which serve as a best alternative for the conventional energy sources. Solar is considered to be the efficient one, because of its easy availability and pollution free nature among the Renewable Energy Sourceslike. The usage of power electronic converters is required due to it is hard to obtain constant voltage from Photovoltaic system because of its sporadic nature. Thus, the paper develops a comprehensive analysis of distinct nature inspired optimization algorithm utilized to improve the performance of Photovoltaic system. Detecting the difficulties faced by the sporadic nature of solar energy and limitations of conventional maximum power point tracking approaches under dynamic and partial shading conditions, the research evaluates many optimization algorithms. Moreover, the integration of advanced algorithms, serves as a development of more effective and adaptive optimization approaches. Additionally, the paper deliberates the benefits, limits and potential areas for future research of each optimization algorithm in the circumstance of Photovoltaic system performance improvement.
Keywords
Renewable Energy Source
Solar
Photovoltaic
Optimization techniques
Comparative analysis
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Journal of Solar Energy Research
Volume 10, Issue 2
Spring 2025
Pages 2415-2436