A novel objective function with artificial ecosystem-based optimization for relieving the mismatching power loss of large-scale photovoltaic array

Ecosystems; Health; Particle swarm optimization (PSO); Photovoltaic cells; Solar power plants; Artificial ecosystems; Objective functions; Optimization algorithms; Particle swarm optimizers; Photovoltaic arrays; Photovoltaic power; Uniform dispersions; Wilcoxon signed rank test; Solar power generati...

Full description

Saved in:
Bibliographic Details
Main Authors: Yousri D., Babu T.S., Mirjalili S., Rajasekar N., Elaziz M.A.
Other Authors: 56688582500
Format: Article
Published: Elsevier Ltd 2023
Tags: Add Tag
No Tags, Be the first to tag this record!
id my.uniten.dspace-25132
record_format dspace
spelling my.uniten.dspace-251322023-05-29T16:06:54Z A novel objective function with artificial ecosystem-based optimization for relieving the mismatching power loss of large-scale photovoltaic array Yousri D. Babu T.S. Mirjalili S. Rajasekar N. Elaziz M.A. 56688582500 56267551500 51461922300 35090434600 57195591068 Ecosystems; Health; Particle swarm optimization (PSO); Photovoltaic cells; Solar power plants; Artificial ecosystems; Objective functions; Optimization algorithms; Particle swarm optimizers; Photovoltaic arrays; Photovoltaic power; Uniform dispersions; Wilcoxon signed rank test; Solar power generation Harvesting maximum power from a partially shaded photovoltaic array is a critical issue that attracts the attention of several researchers. As per the literature, it is found that providing an optimal reconfigured pattern of the shaded photovoltaic array is an optimal solution for this issue. Therefore, in this paper, an innovative fitness function has been considered with the artificial ecosystem-based optimization for an electrical photovoltaic array reconfiguration approach. The proposed approach has been applied for the large scale photovoltaic arrays including 9 �9,6�20,16�16, and 25 � 25 photovoltaic array with different shade patterns. The new fitness function has been validated via a comparison with the regular used weighted function in literature. The quality of the solutions of the proposed artificial ecosystem-based optimization�reconfiguration approach has been assessed and demonstrated via performing several measures namely fill factor, percentage of power loss, mismatch power loss, and power enhancement in comparison with a total cross-tied, particle swarm optimizer approaches, and harris hawks optimizer. Furthermore, the Wilcoxon signed-rank test has been performed to illustrate the applicability, robustness, and consistency of the proposed algorithm results across several independent runs. The analysis reveals the quality of the innovative fitness function while integrating with the optimization algorithms in comparison to the weighted fitness function in producing higher power values via attaining a more efficient photovoltaic array design. Furthermore, the results confirmed the efficiency of the artificial ecosystem-based optimization�photovoltaic reconfiguration approach in boosting the generated photovoltaic power by a percentage of 28.688%, 7.0197 %, 29.2565%, 8.3811% and 5.3884 % across the considered systems with an uniform dispersion of the shadow on the photovoltaic surface and providing highest consistent in the maximum power values across the independent runs. � 2020 Elsevier Ltd Final 2023-05-29T08:06:54Z 2023-05-29T08:06:54Z 2020 Article 10.1016/j.enconman.2020.113385 2-s2.0-85090737570 https://www.scopus.com/inward/record.uri?eid=2-s2.0-85090737570&doi=10.1016%2fj.enconman.2020.113385&partnerID=40&md5=6807ed6376357614dd02eb3e9c84a0e4 https://irepository.uniten.edu.my/handle/123456789/25132 225 113385 All Open Access, Green Elsevier Ltd Scopus
institution Universiti Tenaga Nasional
building UNITEN Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Tenaga Nasional
content_source UNITEN Institutional Repository
url_provider http://dspace.uniten.edu.my/
description Ecosystems; Health; Particle swarm optimization (PSO); Photovoltaic cells; Solar power plants; Artificial ecosystems; Objective functions; Optimization algorithms; Particle swarm optimizers; Photovoltaic arrays; Photovoltaic power; Uniform dispersions; Wilcoxon signed rank test; Solar power generation
author2 56688582500
author_facet 56688582500
Yousri D.
Babu T.S.
Mirjalili S.
Rajasekar N.
Elaziz M.A.
format Article
author Yousri D.
Babu T.S.
Mirjalili S.
Rajasekar N.
Elaziz M.A.
spellingShingle Yousri D.
Babu T.S.
Mirjalili S.
Rajasekar N.
Elaziz M.A.
A novel objective function with artificial ecosystem-based optimization for relieving the mismatching power loss of large-scale photovoltaic array
author_sort Yousri D.
title A novel objective function with artificial ecosystem-based optimization for relieving the mismatching power loss of large-scale photovoltaic array
title_short A novel objective function with artificial ecosystem-based optimization for relieving the mismatching power loss of large-scale photovoltaic array
title_full A novel objective function with artificial ecosystem-based optimization for relieving the mismatching power loss of large-scale photovoltaic array
title_fullStr A novel objective function with artificial ecosystem-based optimization for relieving the mismatching power loss of large-scale photovoltaic array
title_full_unstemmed A novel objective function with artificial ecosystem-based optimization for relieving the mismatching power loss of large-scale photovoltaic array
title_sort novel objective function with artificial ecosystem-based optimization for relieving the mismatching power loss of large-scale photovoltaic array
publisher Elsevier Ltd
publishDate 2023
_version_ 1806424419895083008
score 13.214268