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Identifying and estimating solar cell parameters using an enhanced slime mould algorithm

This study proposed an enhanced slime mould algorithm (ESMA) for identifying the solar cells’ parameters for five photovoltaic (PV) models, making two modifications to the original slime mould algorithm (SMA). The first modification was an arbitrary average position among the new individual position...

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Main Authors: Logeswaary, Devarajah, Mohd Ashraf, Ahmad, Jui, Julakha Jahan
Format: Article
Language:English
English
English
Published: Elsevier 2024
Subjects:
TK Electrical engineering. Electronics Nuclear engineering
Online Access:http://umpir.ump.edu.my/id/eprint/41541/2/Identifying%20and%20estimating%20solar%20cell%20parameters.pdf
http://umpir.ump.edu.my/id/eprint/41541/9/Identifying%20and%20estimating%20solar%20cell%20parameters%20using%20an%20enhanced%20slime%20mould%20algorithm_ABST.pdf
http://umpir.ump.edu.my/id/eprint/41541/10/Identifying%20and%20estimating%20solar%20cell%20parameters%20using%20an%20enhanced%20slime%20mould%20algorithm.pdf
http://umpir.ump.edu.my/id/eprint/41541/
https://doi.org/10.1016/j.ijleo.2024.171890
https://doi.org/10.1016/j.ijleo.2024.171890
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spelling my.ump.umpir.415412024-11-19T01:36:06Z http://umpir.ump.edu.my/id/eprint/41541/ Identifying and estimating solar cell parameters using an enhanced slime mould algorithm Logeswaary, Devarajah Mohd Ashraf, Ahmad Jui, Julakha Jahan TK Electrical engineering. Electronics Nuclear engineering This study proposed an enhanced slime mould algorithm (ESMA) for identifying the solar cells’ parameters for five photovoltaic (PV) models, making two modifications to the original slime mould algorithm (SMA). The first modification was an arbitrary average position among the new individual position of slime and the best individual position of the slime mound currently found to resolve the issue of local optimum. Second, the tangent hyperbolical function of the formula p in the original SMA was replaced with an exponential function to create more variations for selecting the updated equation. The proposed ESMA was used to resolve the problem of estimating PV parameters based on the empirical current-voltage (I-V) data. Specifically, ESMA was evaluated on the parameter estimation in several photovoltaic models, i.e., the one-diode model (ODM), dual-diode model (DDM), and PV-module model (PMM). In general, ESMA outperformed the original SMA and other recent algorithms. Also, in order to provide a close approximation of the empirical I-V data of the real PV modules and cells, ESMA was able to determine the optimal parameter values for photovoltaic models. Elsevier 2024-09 Article PeerReviewed pdf en http://umpir.ump.edu.my/id/eprint/41541/2/Identifying%20and%20estimating%20solar%20cell%20parameters.pdf pdf en http://umpir.ump.edu.my/id/eprint/41541/9/Identifying%20and%20estimating%20solar%20cell%20parameters%20using%20an%20enhanced%20slime%20mould%20algorithm_ABST.pdf pdf en http://umpir.ump.edu.my/id/eprint/41541/10/Identifying%20and%20estimating%20solar%20cell%20parameters%20using%20an%20enhanced%20slime%20mould%20algorithm.pdf Logeswaary, Devarajah and Mohd Ashraf, Ahmad and Jui, Julakha Jahan (2024) Identifying and estimating solar cell parameters using an enhanced slime mould algorithm. Optik, 311 (171890). pp. 1-22. ISSN 1618-1336. (Published) https://doi.org/10.1016/j.ijleo.2024.171890 https://doi.org/10.1016/j.ijleo.2024.171890
institution Universiti Malaysia Pahang Al-Sultan Abdullah
building UMPSA Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Malaysia Pahang Al-Sultan Abdullah
content_source UMPSA Institutional Repository
url_provider http://umpir.ump.edu.my/
language English
English
English
topic TK Electrical engineering. Electronics Nuclear engineering
spellingShingle TK Electrical engineering. Electronics Nuclear engineering
Logeswaary, Devarajah
Mohd Ashraf, Ahmad
Jui, Julakha Jahan
Identifying and estimating solar cell parameters using an enhanced slime mould algorithm
description This study proposed an enhanced slime mould algorithm (ESMA) for identifying the solar cells’ parameters for five photovoltaic (PV) models, making two modifications to the original slime mould algorithm (SMA). The first modification was an arbitrary average position among the new individual position of slime and the best individual position of the slime mound currently found to resolve the issue of local optimum. Second, the tangent hyperbolical function of the formula p in the original SMA was replaced with an exponential function to create more variations for selecting the updated equation. The proposed ESMA was used to resolve the problem of estimating PV parameters based on the empirical current-voltage (I-V) data. Specifically, ESMA was evaluated on the parameter estimation in several photovoltaic models, i.e., the one-diode model (ODM), dual-diode model (DDM), and PV-module model (PMM). In general, ESMA outperformed the original SMA and other recent algorithms. Also, in order to provide a close approximation of the empirical I-V data of the real PV modules and cells, ESMA was able to determine the optimal parameter values for photovoltaic models.
format Article
author Logeswaary, Devarajah
Mohd Ashraf, Ahmad
Jui, Julakha Jahan
author_facet Logeswaary, Devarajah
Mohd Ashraf, Ahmad
Jui, Julakha Jahan
author_sort Logeswaary, Devarajah
title Identifying and estimating solar cell parameters using an enhanced slime mould algorithm
title_short Identifying and estimating solar cell parameters using an enhanced slime mould algorithm
title_full Identifying and estimating solar cell parameters using an enhanced slime mould algorithm
title_fullStr Identifying and estimating solar cell parameters using an enhanced slime mould algorithm
title_full_unstemmed Identifying and estimating solar cell parameters using an enhanced slime mould algorithm
title_sort identifying and estimating solar cell parameters using an enhanced slime mould algorithm
publisher Elsevier
publishDate 2024
url http://umpir.ump.edu.my/id/eprint/41541/2/Identifying%20and%20estimating%20solar%20cell%20parameters.pdf
http://umpir.ump.edu.my/id/eprint/41541/9/Identifying%20and%20estimating%20solar%20cell%20parameters%20using%20an%20enhanced%20slime%20mould%20algorithm_ABST.pdf
http://umpir.ump.edu.my/id/eprint/41541/10/Identifying%20and%20estimating%20solar%20cell%20parameters%20using%20an%20enhanced%20slime%20mould%20algorithm.pdf
http://umpir.ump.edu.my/id/eprint/41541/
https://doi.org/10.1016/j.ijleo.2024.171890
https://doi.org/10.1016/j.ijleo.2024.171890
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score 13.232389

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