Fault Detection and Classification of a Photovoltaic Generator Using the BES Optimization Algorithm Associated with SVM
In this work, an innovative approach based on the estimation of the photovoltaic generator (GPV) parameters from the Bald Eagle Search (BES) optimization algorithm, associated with a support vector machine (SVM) classification algorithm, allowed to highlight a new tool for the classification of the...
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| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
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Wiley
2022-01-01
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| Series: | International Journal of Photoenergy |
| Online Access: | http://dx.doi.org/10.1155/2022/6841861 |
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| _version_ | 1832552942074331136 |
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| author | R. J. Koloko Koloko P. Ele R. Wamkeue A. Melingui |
| author_facet | R. J. Koloko Koloko P. Ele R. Wamkeue A. Melingui |
| author_sort | R. J. Koloko Koloko |
| collection | DOAJ |
| description | In this work, an innovative approach based on the estimation of the photovoltaic generator (GPV) parameters from the Bald Eagle Search (BES) optimization algorithm, associated with a support vector machine (SVM) classification algorithm, allowed to highlight a new tool for the classification of the signatures of shading and moisture PV defects. It recognizes signatures generated by the GPV in healthy and erroneous operation using the optimized parametric vector and classifies defects using the same optimized vector. The technique emphasizes the resilience of parameter estimate in terms of error on all parameters. The classification accuracy is 93%. The residuals between the estimated curve in healthy operation with a minimum error of the order of 10-4 and the one at fault are used as an indicator of faults. |
| format | Article |
| id | doaj-art-c0de9e3271184452b0215f5fe0c7630a |
| institution | Kabale University |
| issn | 1687-529X |
| language | English |
| publishDate | 2022-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | International Journal of Photoenergy |
| spelling | doaj-art-c0de9e3271184452b0215f5fe0c7630a2025-02-03T05:57:29ZengWileyInternational Journal of Photoenergy1687-529X2022-01-01202210.1155/2022/6841861Fault Detection and Classification of a Photovoltaic Generator Using the BES Optimization Algorithm Associated with SVMR. J. Koloko Koloko0P. Ele1R. Wamkeue2A. Melingui3Laboratory of Electrical EngineeringLaboratory of Electrical EngineeringLaboratory of Electrical EngineeringLaboratory of Electrical EngineeringIn this work, an innovative approach based on the estimation of the photovoltaic generator (GPV) parameters from the Bald Eagle Search (BES) optimization algorithm, associated with a support vector machine (SVM) classification algorithm, allowed to highlight a new tool for the classification of the signatures of shading and moisture PV defects. It recognizes signatures generated by the GPV in healthy and erroneous operation using the optimized parametric vector and classifies defects using the same optimized vector. The technique emphasizes the resilience of parameter estimate in terms of error on all parameters. The classification accuracy is 93%. The residuals between the estimated curve in healthy operation with a minimum error of the order of 10-4 and the one at fault are used as an indicator of faults.http://dx.doi.org/10.1155/2022/6841861 |
| spellingShingle | R. J. Koloko Koloko P. Ele R. Wamkeue A. Melingui Fault Detection and Classification of a Photovoltaic Generator Using the BES Optimization Algorithm Associated with SVM International Journal of Photoenergy |
| title | Fault Detection and Classification of a Photovoltaic Generator Using the BES Optimization Algorithm Associated with SVM |
| title_full | Fault Detection and Classification of a Photovoltaic Generator Using the BES Optimization Algorithm Associated with SVM |
| title_fullStr | Fault Detection and Classification of a Photovoltaic Generator Using the BES Optimization Algorithm Associated with SVM |
| title_full_unstemmed | Fault Detection and Classification of a Photovoltaic Generator Using the BES Optimization Algorithm Associated with SVM |
| title_short | Fault Detection and Classification of a Photovoltaic Generator Using the BES Optimization Algorithm Associated with SVM |
| title_sort | fault detection and classification of a photovoltaic generator using the bes optimization algorithm associated with svm |
| url | http://dx.doi.org/10.1155/2022/6841861 |
| work_keys_str_mv | AT rjkolokokoloko faultdetectionandclassificationofaphotovoltaicgeneratorusingthebesoptimizationalgorithmassociatedwithsvm AT pele faultdetectionandclassificationofaphotovoltaicgeneratorusingthebesoptimizationalgorithmassociatedwithsvm AT rwamkeue faultdetectionandclassificationofaphotovoltaicgeneratorusingthebesoptimizationalgorithmassociatedwithsvm AT amelingui faultdetectionandclassificationofaphotovoltaicgeneratorusingthebesoptimizationalgorithmassociatedwithsvm |