Parameter Identification in Triple-Diode Photovoltaic Modules Using Hybrid Optimization Algorithms
Identifying the parameters of a triple-diode electrical circuit structure in PV modules is a critical issue, and it has been regarded as an important research area. Accordingly, in this study, a differential evolution algorithm (DEA) is hybridized with an electromagnetism-like algorithm (EMA) in the...
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MDPI AG
2024-11-01
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| Series: | Designs |
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| Online Access: | https://www.mdpi.com/2411-9660/8/6/119 |
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| author | Dhiaa Halboot Muhsen Haider Tarish Haider Yaarob Al-Nidawi |
| author_facet | Dhiaa Halboot Muhsen Haider Tarish Haider Yaarob Al-Nidawi |
| author_sort | Dhiaa Halboot Muhsen |
| collection | DOAJ |
| description | Identifying the parameters of a triple-diode electrical circuit structure in PV modules is a critical issue, and it has been regarded as an important research area. Accordingly, in this study, a differential evolution algorithm (DEA) is hybridized with an electromagnetism-like algorithm (EMA) in the mutation stage to enhance the reliability and efficiency of the DEA. A new formula is presented to adapt the control parameters (mutation factor and crossover rate) of the DEA. Seven different experimental data sets are used to improve the performance of the proposed differential evolution with an integrated mutation per iteration algorithm (DEIMA). The results of the proposed PV modeling method are evaluated with other state-of-the-art approaches. According to different statistical criteria, the DEIMA demonstrates superiority in terms of root mean square error and main bias error by at least 5.4% and 10%, respectively, as compared to other methods. Furthermore, the DEIMA has an average execution time of 27.69 s, which is less than that of the other methods. |
| format | Article |
| id | doaj-art-55869182fdbf438883669303d74a0063 |
| institution | DOAJ |
| issn | 2411-9660 |
| language | English |
| publishDate | 2024-11-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Designs |
| spelling | doaj-art-55869182fdbf438883669303d74a00632025-08-20T02:55:56ZengMDPI AGDesigns2411-96602024-11-018611910.3390/designs8060119Parameter Identification in Triple-Diode Photovoltaic Modules Using Hybrid Optimization AlgorithmsDhiaa Halboot Muhsen0Haider Tarish Haider1Yaarob Al-Nidawi2Department of Computer Engineering, Mustansiriyah University, Baghdad 14022, IraqDepartment of Computer Engineering, Mustansiriyah University, Baghdad 14022, IraqDepartment of Computer Engineering, Mustansiriyah University, Baghdad 14022, IraqIdentifying the parameters of a triple-diode electrical circuit structure in PV modules is a critical issue, and it has been regarded as an important research area. Accordingly, in this study, a differential evolution algorithm (DEA) is hybridized with an electromagnetism-like algorithm (EMA) in the mutation stage to enhance the reliability and efficiency of the DEA. A new formula is presented to adapt the control parameters (mutation factor and crossover rate) of the DEA. Seven different experimental data sets are used to improve the performance of the proposed differential evolution with an integrated mutation per iteration algorithm (DEIMA). The results of the proposed PV modeling method are evaluated with other state-of-the-art approaches. According to different statistical criteria, the DEIMA demonstrates superiority in terms of root mean square error and main bias error by at least 5.4% and 10%, respectively, as compared to other methods. Furthermore, the DEIMA has an average execution time of 27.69 s, which is less than that of the other methods.https://www.mdpi.com/2411-9660/8/6/119differential evolutionelectromagnetism-likephotovoltaictriple-diode modeloptimizationsolar irradiance |
| spellingShingle | Dhiaa Halboot Muhsen Haider Tarish Haider Yaarob Al-Nidawi Parameter Identification in Triple-Diode Photovoltaic Modules Using Hybrid Optimization Algorithms Designs differential evolution electromagnetism-like photovoltaic triple-diode model optimization solar irradiance |
| title | Parameter Identification in Triple-Diode Photovoltaic Modules Using Hybrid Optimization Algorithms |
| title_full | Parameter Identification in Triple-Diode Photovoltaic Modules Using Hybrid Optimization Algorithms |
| title_fullStr | Parameter Identification in Triple-Diode Photovoltaic Modules Using Hybrid Optimization Algorithms |
| title_full_unstemmed | Parameter Identification in Triple-Diode Photovoltaic Modules Using Hybrid Optimization Algorithms |
| title_short | Parameter Identification in Triple-Diode Photovoltaic Modules Using Hybrid Optimization Algorithms |
| title_sort | parameter identification in triple diode photovoltaic modules using hybrid optimization algorithms |
| topic | differential evolution electromagnetism-like photovoltaic triple-diode model optimization solar irradiance |
| url | https://www.mdpi.com/2411-9660/8/6/119 |
| work_keys_str_mv | AT dhiaahalbootmuhsen parameteridentificationintriplediodephotovoltaicmodulesusinghybridoptimizationalgorithms AT haidertarishhaider parameteridentificationintriplediodephotovoltaicmodulesusinghybridoptimizationalgorithms AT yaarobalnidawi parameteridentificationintriplediodephotovoltaicmodulesusinghybridoptimizationalgorithms |