Research on Characteristic Analysis and Identification Methods for DC-Side Grounding Faults in Grid-Connected Photovoltaic Inverters
The analysis and accurate identification of DC-side grounding faults in grid-connected photovoltaic (PV) inverters is a critical step in enhancing operation and maintenance capabilities and ensuring the safe operation of PV grid-connected systems. However, the characteristics of DC-side grounding fa...
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MDPI AG
2025-06-01
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| Series: | Energies |
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| Online Access: | https://www.mdpi.com/1996-1073/18/13/3243 |
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| author | Wanli Feng Lei Su Cao Kan Mingjiang Wei Changlong Li |
| author_facet | Wanli Feng Lei Su Cao Kan Mingjiang Wei Changlong Li |
| author_sort | Wanli Feng |
| collection | DOAJ |
| description | The analysis and accurate identification of DC-side grounding faults in grid-connected photovoltaic (PV) inverters is a critical step in enhancing operation and maintenance capabilities and ensuring the safe operation of PV grid-connected systems. However, the characteristics of DC-side grounding faults remain unclear, and effective methods for identifying such faults are lacking. To address the need for leakage characteristic analysis and fault identification of DC-side grounding faults in grid-connected PV inverters, this paper first establishes an equivalent analysis model for DC-side grounding faults in three-phase grid-connected inverters. The formation mechanism and frequency-domain characteristics of residual current under DC-side fault conditions are analyzed, and the specific causes of different frequency components in the residual current are identified. Based on the leakage current mechanisms and statistical characteristics of grid-connected PV inverters, a multi-type DC-side grounding fault identification method is proposed using the light gradient-boosting machine (LGBM) algorithm. In the simulation case study, the proposed fault identification method, which combines mechanism characteristics and statistical characteristics, achieved an accuracy rate of 99%, which was significantly superior to traditional methods based solely on statistical characteristics and other machine learning algorithms. Real-time simulation verification shows that introducing mechanism-based features into grid-connected photovoltaic inverters can significantly improve the accuracy of identifying grounding faults on the DC side. |
| format | Article |
| id | doaj-art-5347336acef24f349fc6f6f66e4e6364 |
| institution | DOAJ |
| issn | 1996-1073 |
| language | English |
| publishDate | 2025-06-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Energies |
| spelling | doaj-art-5347336acef24f349fc6f6f66e4e63642025-08-20T03:16:42ZengMDPI AGEnergies1996-10732025-06-011813324310.3390/en18133243Research on Characteristic Analysis and Identification Methods for DC-Side Grounding Faults in Grid-Connected Photovoltaic InvertersWanli Feng0Lei Su1Cao Kan2Mingjiang Wei3Changlong Li4State Grid Hubei Electric Power Research Institute, Wuhan 430074, ChinaState Grid Hubei Electric Power Research Institute, Wuhan 430074, ChinaState Grid Hubei Electric Power Research Institute, Wuhan 430074, ChinaState Grid Hubei Electric Power Research Institute, Wuhan 430074, ChinaSchool of Electrical and Information Engineering, Changsha University of Science and Technology, Changsha 410014, ChinaThe analysis and accurate identification of DC-side grounding faults in grid-connected photovoltaic (PV) inverters is a critical step in enhancing operation and maintenance capabilities and ensuring the safe operation of PV grid-connected systems. However, the characteristics of DC-side grounding faults remain unclear, and effective methods for identifying such faults are lacking. To address the need for leakage characteristic analysis and fault identification of DC-side grounding faults in grid-connected PV inverters, this paper first establishes an equivalent analysis model for DC-side grounding faults in three-phase grid-connected inverters. The formation mechanism and frequency-domain characteristics of residual current under DC-side fault conditions are analyzed, and the specific causes of different frequency components in the residual current are identified. Based on the leakage current mechanisms and statistical characteristics of grid-connected PV inverters, a multi-type DC-side grounding fault identification method is proposed using the light gradient-boosting machine (LGBM) algorithm. In the simulation case study, the proposed fault identification method, which combines mechanism characteristics and statistical characteristics, achieved an accuracy rate of 99%, which was significantly superior to traditional methods based solely on statistical characteristics and other machine learning algorithms. Real-time simulation verification shows that introducing mechanism-based features into grid-connected photovoltaic inverters can significantly improve the accuracy of identifying grounding faults on the DC side.https://www.mdpi.com/1996-1073/18/13/3243photovoltaic grid-connected inverterDC-side grounding faultmechanistic characteristicsstatistical featuresfault diagnosisLGBM algorithm |
| spellingShingle | Wanli Feng Lei Su Cao Kan Mingjiang Wei Changlong Li Research on Characteristic Analysis and Identification Methods for DC-Side Grounding Faults in Grid-Connected Photovoltaic Inverters Energies photovoltaic grid-connected inverter DC-side grounding fault mechanistic characteristics statistical features fault diagnosis LGBM algorithm |
| title | Research on Characteristic Analysis and Identification Methods for DC-Side Grounding Faults in Grid-Connected Photovoltaic Inverters |
| title_full | Research on Characteristic Analysis and Identification Methods for DC-Side Grounding Faults in Grid-Connected Photovoltaic Inverters |
| title_fullStr | Research on Characteristic Analysis and Identification Methods for DC-Side Grounding Faults in Grid-Connected Photovoltaic Inverters |
| title_full_unstemmed | Research on Characteristic Analysis and Identification Methods for DC-Side Grounding Faults in Grid-Connected Photovoltaic Inverters |
| title_short | Research on Characteristic Analysis and Identification Methods for DC-Side Grounding Faults in Grid-Connected Photovoltaic Inverters |
| title_sort | research on characteristic analysis and identification methods for dc side grounding faults in grid connected photovoltaic inverters |
| topic | photovoltaic grid-connected inverter DC-side grounding fault mechanistic characteristics statistical features fault diagnosis LGBM algorithm |
| url | https://www.mdpi.com/1996-1073/18/13/3243 |
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