Principal Component Analysis-Based Shading Defect Identification and Categorization in Standalone PV Systems Using I-V Curves
Photovoltaic (PV) system health monitoring and fault diagnosis are essential for optimizing power generation, enhancing reliability, and prolonging the lifespan of PV power plants. Shading, especially in PV systems, leads to unique voltage-current (I-V) characteristics, serving as indicators of syst...
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| Format: | Article |
| Language: | English |
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University of El Oued
2023-12-01
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| Series: | International Journal of Energetica |
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| Online Access: | https://www.ijeca.info/index.php/IJECA/article/view/222 |
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| author | Hayder Dakhil Atiyah Mohamed Boukattaya Fatma Bensalem |
| author_facet | Hayder Dakhil Atiyah Mohamed Boukattaya Fatma Bensalem |
| author_sort | Hayder Dakhil Atiyah |
| collection | DOAJ |
| description | Photovoltaic (PV) system health monitoring and fault diagnosis are essential for optimizing power generation, enhancing reliability, and prolonging the lifespan of PV power plants. Shading, especially in PV systems, leads to unique voltage-current (I-V) characteristics, serving as indicators of system health. This paper presents a cost-effective and highly accurate method for detecting, diagnosing, and classifying shading faults based on real I-V data obtained through electrical measurements under both healthy and shaded conditions. The method leverages Principal Component Analysis (PCA) to separate classes, and a confusion matrix assesses classification accuracy. The results demonstrate a success rate exceeding 98% in various configurations, using experimental data from a 250 W PV module. Importantly, this method relies solely on existing electrical measurements, eliminating the need for additional sensors, making it both efficient and cost-effective. |
| format | Article |
| id | doaj-art-9ff8ebc5c4064e76ac85c9e75cc6be73 |
| institution | Kabale University |
| issn | 2543-3717 |
| language | English |
| publishDate | 2023-12-01 |
| publisher | University of El Oued |
| record_format | Article |
| series | International Journal of Energetica |
| spelling | doaj-art-9ff8ebc5c4064e76ac85c9e75cc6be732025-08-20T03:38:27ZengUniversity of El OuedInternational Journal of Energetica2543-37172023-12-01824453140Principal Component Analysis-Based Shading Defect Identification and Categorization in Standalone PV Systems Using I-V CurvesHayder Dakhil Atiyah0Mohamed Boukattaya1Fatma Bensalem2Department electrical power at National School of Engineering of SfaxLaboratory (Lab-STA), ENIS SfaxLaboratory (CEMLab), ENIS Sfax UniversityPhotovoltaic (PV) system health monitoring and fault diagnosis are essential for optimizing power generation, enhancing reliability, and prolonging the lifespan of PV power plants. Shading, especially in PV systems, leads to unique voltage-current (I-V) characteristics, serving as indicators of system health. This paper presents a cost-effective and highly accurate method for detecting, diagnosing, and classifying shading faults based on real I-V data obtained through electrical measurements under both healthy and shaded conditions. The method leverages Principal Component Analysis (PCA) to separate classes, and a confusion matrix assesses classification accuracy. The results demonstrate a success rate exceeding 98% in various configurations, using experimental data from a 250 W PV module. Importantly, this method relies solely on existing electrical measurements, eliminating the need for additional sensors, making it both efficient and cost-effective.https://www.ijeca.info/index.php/IJECA/article/view/222pv model, principal component analysis, health system, temperature, irradiation |
| spellingShingle | Hayder Dakhil Atiyah Mohamed Boukattaya Fatma Bensalem Principal Component Analysis-Based Shading Defect Identification and Categorization in Standalone PV Systems Using I-V Curves International Journal of Energetica pv model, principal component analysis, health system, temperature, irradiation |
| title | Principal Component Analysis-Based Shading Defect Identification and Categorization in Standalone PV Systems Using I-V Curves |
| title_full | Principal Component Analysis-Based Shading Defect Identification and Categorization in Standalone PV Systems Using I-V Curves |
| title_fullStr | Principal Component Analysis-Based Shading Defect Identification and Categorization in Standalone PV Systems Using I-V Curves |
| title_full_unstemmed | Principal Component Analysis-Based Shading Defect Identification and Categorization in Standalone PV Systems Using I-V Curves |
| title_short | Principal Component Analysis-Based Shading Defect Identification and Categorization in Standalone PV Systems Using I-V Curves |
| title_sort | principal component analysis based shading defect identification and categorization in standalone pv systems using i v curves |
| topic | pv model, principal component analysis, health system, temperature, irradiation |
| url | https://www.ijeca.info/index.php/IJECA/article/view/222 |
| work_keys_str_mv | AT hayderdakhilatiyah principalcomponentanalysisbasedshadingdefectidentificationandcategorizationinstandalonepvsystemsusingivcurves AT mohamedboukattaya principalcomponentanalysisbasedshadingdefectidentificationandcategorizationinstandalonepvsystemsusingivcurves AT fatmabensalem principalcomponentanalysisbasedshadingdefectidentificationandcategorizationinstandalonepvsystemsusingivcurves |