Unified Fuzzy Logic Based Approach for Detection and Classification of PV Faults Using I-V Trend Line
Solar photovoltaic PV plants worldwide are continuously monitored and carefully protected to ensure safe and reliable operation through detecting and isolating faults. Faults are very common in modern solar PV systems which interrupt normal system operation adversely affecting the performance of the...
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| Format: | Article |
| Language: | English |
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MDPI AG
2022-07-01
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| Series: | Energies |
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| Online Access: | https://www.mdpi.com/1996-1073/15/14/5106 |
| _version_ | 1827597290271932416 |
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| author | Imran Hussain Ihsan Ullah Khalil Aqsa Islam Mati Ullah Ahsan Taosif Iqbal Md. Shahariar Chowdhury Kuaanan Techato Nasim Ullah |
| author_facet | Imran Hussain Ihsan Ullah Khalil Aqsa Islam Mati Ullah Ahsan Taosif Iqbal Md. Shahariar Chowdhury Kuaanan Techato Nasim Ullah |
| author_sort | Imran Hussain |
| collection | DOAJ |
| description | Solar photovoltaic PV plants worldwide are continuously monitored and carefully protected to ensure safe and reliable operation through detecting and isolating faults. Faults are very common in modern solar PV systems which interrupt normal system operation adversely affecting the performance of the PV systems. When undetected, faults not only cause significant reduction in the efficiency and life span of the PV system, but also result in damage and fire hazards compromising their reliability. Therefore, early fault detection and diagnosis of photovoltaic plants is a necessity for safe and reliable operation required for growing solar PV systems. Unfortunately, several recent fire incidents have been reported recently caused by undetected faults in solar PV systems. Motivated by this challenge, this paper, utilizing a proposed fuzzy logic algorithm, presents a novel technique for detecting and classifying faults in solar PV systems. Furthermore, the proposed method introduces fault indexing as a performance indicator that measures the degree of deviation from the normal operating conditions of the photovoltaic system. Various signatures of each fault scenario are identified in the shape of corresponding current-voltage trajectories and their extracted parameters. The effectiveness of the proposed technique is evaluated both in simulation and experimentally using a 5 kW grid connected solar array. It is demonstrated that the proposed technique is capable of diagnosing the occurrence of different faults with more than 98% accuracy. |
| first_indexed | 2024-03-09T03:28:08Z |
| format | Article |
| id | doaj.art-28e4f4739a6344b293c55fb6362b0bc6 |
| institution | Directory Open Access Journal |
| issn | 1996-1073 |
| language | English |
| last_indexed | 2024-03-09T03:28:08Z |
| publishDate | 2022-07-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Energies |
| spelling | doaj.art-28e4f4739a6344b293c55fb6362b0bc62023-12-03T14:59:00ZengMDPI AGEnergies1996-10732022-07-011514510610.3390/en15145106Unified Fuzzy Logic Based Approach for Detection and Classification of PV Faults Using I-V Trend LineImran Hussain0Ihsan Ullah Khalil1Aqsa Islam2Mati Ullah Ahsan3Taosif Iqbal4Md. Shahariar Chowdhury5Kuaanan Techato6Nasim Ullah7Department of Electrical Engineering, University of Engineering and Technology, Taxila 47050, PakistanCollege of Electrical and Mechanical Engineering, National University of Sciences and Technology, Islamabad 44000, PakistanDepartment of Physics, University of Agriculture, Faisalabad 38000, PakistanDepartment of Electrical Engineering, Universiti Tun Hussein Onn Malaysia (UTHM), Parit Raja, Batu Pahat 86400, MalaysiaCollege of Electrical and Mechanical Engineering, National University of Sciences and Technology, Islamabad 44000, PakistanFaculties Environmental Management, Prince of Songkla University, Songkhla 90110, ThailandFaculties Environmental Management, Prince of Songkla University, Songkhla 90110, ThailandDepartment of Electrical Engineering, College of Engineering, Taif University, P.O. Box 11099, Taif 21944, Saudi ArabiaSolar photovoltaic PV plants worldwide are continuously monitored and carefully protected to ensure safe and reliable operation through detecting and isolating faults. Faults are very common in modern solar PV systems which interrupt normal system operation adversely affecting the performance of the PV systems. When undetected, faults not only cause significant reduction in the efficiency and life span of the PV system, but also result in damage and fire hazards compromising their reliability. Therefore, early fault detection and diagnosis of photovoltaic plants is a necessity for safe and reliable operation required for growing solar PV systems. Unfortunately, several recent fire incidents have been reported recently caused by undetected faults in solar PV systems. Motivated by this challenge, this paper, utilizing a proposed fuzzy logic algorithm, presents a novel technique for detecting and classifying faults in solar PV systems. Furthermore, the proposed method introduces fault indexing as a performance indicator that measures the degree of deviation from the normal operating conditions of the photovoltaic system. Various signatures of each fault scenario are identified in the shape of corresponding current-voltage trajectories and their extracted parameters. The effectiveness of the proposed technique is evaluated both in simulation and experimentally using a 5 kW grid connected solar array. It is demonstrated that the proposed technique is capable of diagnosing the occurrence of different faults with more than 98% accuracy.https://www.mdpi.com/1996-1073/15/14/5106fuzzy logic controller (FLC)fault detection and diagnosis (FDD)machine learning (ML)photovoltaic (PV) systems |
| spellingShingle | Imran Hussain Ihsan Ullah Khalil Aqsa Islam Mati Ullah Ahsan Taosif Iqbal Md. Shahariar Chowdhury Kuaanan Techato Nasim Ullah Unified Fuzzy Logic Based Approach for Detection and Classification of PV Faults Using I-V Trend Line Energies fuzzy logic controller (FLC) fault detection and diagnosis (FDD) machine learning (ML) photovoltaic (PV) systems |
| title | Unified Fuzzy Logic Based Approach for Detection and Classification of PV Faults Using I-V Trend Line |
| title_full | Unified Fuzzy Logic Based Approach for Detection and Classification of PV Faults Using I-V Trend Line |
| title_fullStr | Unified Fuzzy Logic Based Approach for Detection and Classification of PV Faults Using I-V Trend Line |
| title_full_unstemmed | Unified Fuzzy Logic Based Approach for Detection and Classification of PV Faults Using I-V Trend Line |
| title_short | Unified Fuzzy Logic Based Approach for Detection and Classification of PV Faults Using I-V Trend Line |
| title_sort | unified fuzzy logic based approach for detection and classification of pv faults using i v trend line |
| topic | fuzzy logic controller (FLC) fault detection and diagnosis (FDD) machine learning (ML) photovoltaic (PV) systems |
| url | https://www.mdpi.com/1996-1073/15/14/5106 |
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