Optimal equivalent circuit models for photovoltaic cells and modules using multi-source guided teaching–learning-based optimization
The complexity of equivalent circuit models of photovoltaic cells and modules poses a difficult task to the parameter extraction methods. Teaching-learning-based optimization (TLBO) is a potent metaheuristic-based parameter extraction method, but it suffers from insufficient precision and low depend...
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| Format: | Article |
| Language: | English |
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Elsevier
2024-11-01
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| Series: | Ain Shams Engineering Journal |
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| Online Access: | http://www.sciencedirect.com/science/article/pii/S2090447924003630 |
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| author | Yasha Li Guojiang Xiong Seyedali Mirjalili Ali Wagdy Mohamed |
| author_facet | Yasha Li Guojiang Xiong Seyedali Mirjalili Ali Wagdy Mohamed |
| author_sort | Yasha Li |
| collection | DOAJ |
| description | The complexity of equivalent circuit models of photovoltaic cells and modules poses a difficult task to the parameter extraction methods. Teaching-learning-based optimization (TLBO) is a potent metaheuristic-based parameter extraction method, but it suffers from insufficient precision and low dependability. This study presented a multi-source guided TLBO through improving its two optimization phases. A multi-source guided approach with one-to-one and step-by-step teaching strategies was designed to guide different learners in the teacher phase. Besides, different strategies based on multiple learners were introduced for learners with different knowledge reserves to strengthen information exchanging. With the improvements, it is advantageous to lessen the likelihood of hitting a local optimum and thereby the global convergence can be accelerated. The resultant method was verified on single diode model, double diode model, and three additional modules. The findings demonstrate that it obtained better solutions in precision and dependability, and stood out from the crowd of algorithms. |
| format | Article |
| id | doaj-art-6b7ecd1ff6a2448fb80bce8f6bcb5728 |
| institution | Kabale University |
| issn | 2090-4479 |
| language | English |
| publishDate | 2024-11-01 |
| publisher | Elsevier |
| record_format | Article |
| series | Ain Shams Engineering Journal |
| spelling | doaj-art-6b7ecd1ff6a2448fb80bce8f6bcb57282024-11-18T04:32:51ZengElsevierAin Shams Engineering Journal2090-44792024-11-011511102988Optimal equivalent circuit models for photovoltaic cells and modules using multi-source guided teaching–learning-based optimizationYasha Li0Guojiang Xiong1Seyedali Mirjalili2Ali Wagdy Mohamed3College of Electrical Engineering, Guizhou University, Guiyang 550025, ChinaCollege of Electrical Engineering, Guizhou University, Guiyang 550025, China; Key Laboratory of Industrial Internet of Things & Networked Control, Ministry of Education, Chongqing 400065, China; Corresponding author at: Room #402, College of Electrical Engineering, Guizhou University, Jiaxiu South Road, Huaxi District, Guiyang City, Guizhou Province, China.Centre for Artificial Intelligence Research and Optimisation, Torrens University Australia, Brisbane, AustraliaOperations Research Department, Faculty of Graduate Studies for Statistical Research, Cairo University, Giza 12613, Egypt; University of Science and Technology, School of Business, Zewail City of Science and Technology, 6th of October City, Giza, 12588, EgyptThe complexity of equivalent circuit models of photovoltaic cells and modules poses a difficult task to the parameter extraction methods. Teaching-learning-based optimization (TLBO) is a potent metaheuristic-based parameter extraction method, but it suffers from insufficient precision and low dependability. This study presented a multi-source guided TLBO through improving its two optimization phases. A multi-source guided approach with one-to-one and step-by-step teaching strategies was designed to guide different learners in the teacher phase. Besides, different strategies based on multiple learners were introduced for learners with different knowledge reserves to strengthen information exchanging. With the improvements, it is advantageous to lessen the likelihood of hitting a local optimum and thereby the global convergence can be accelerated. The resultant method was verified on single diode model, double diode model, and three additional modules. The findings demonstrate that it obtained better solutions in precision and dependability, and stood out from the crowd of algorithms.http://www.sciencedirect.com/science/article/pii/S2090447924003630Metaheuristic algorithmParameter extractionPhotovoltaic cellTeaching–learning-based optimization |
| spellingShingle | Yasha Li Guojiang Xiong Seyedali Mirjalili Ali Wagdy Mohamed Optimal equivalent circuit models for photovoltaic cells and modules using multi-source guided teaching–learning-based optimization Ain Shams Engineering Journal Metaheuristic algorithm Parameter extraction Photovoltaic cell Teaching–learning-based optimization |
| title | Optimal equivalent circuit models for photovoltaic cells and modules using multi-source guided teaching–learning-based optimization |
| title_full | Optimal equivalent circuit models for photovoltaic cells and modules using multi-source guided teaching–learning-based optimization |
| title_fullStr | Optimal equivalent circuit models for photovoltaic cells and modules using multi-source guided teaching–learning-based optimization |
| title_full_unstemmed | Optimal equivalent circuit models for photovoltaic cells and modules using multi-source guided teaching–learning-based optimization |
| title_short | Optimal equivalent circuit models for photovoltaic cells and modules using multi-source guided teaching–learning-based optimization |
| title_sort | optimal equivalent circuit models for photovoltaic cells and modules using multi source guided teaching learning based optimization |
| topic | Metaheuristic algorithm Parameter extraction Photovoltaic cell Teaching–learning-based optimization |
| url | http://www.sciencedirect.com/science/article/pii/S2090447924003630 |
| work_keys_str_mv | AT yashali optimalequivalentcircuitmodelsforphotovoltaiccellsandmodulesusingmultisourceguidedteachinglearningbasedoptimization AT guojiangxiong optimalequivalentcircuitmodelsforphotovoltaiccellsandmodulesusingmultisourceguidedteachinglearningbasedoptimization AT seyedalimirjalili optimalequivalentcircuitmodelsforphotovoltaiccellsandmodulesusingmultisourceguidedteachinglearningbasedoptimization AT aliwagdymohamed optimalequivalentcircuitmodelsforphotovoltaiccellsandmodulesusingmultisourceguidedteachinglearningbasedoptimization |