Research on fault diagnosis method for photovoltaic array based on GOA-SVM

doi:10.19781/j.issn.1673-9140.2024.05.018

Home > Archive>Volume 39, Issue 5, 2024 >172-180. DOI:10.19781/j.issn.1673-9140.2024.05.018

Research on fault diagnosis method for photovoltaic array based on GOA-SVM
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                        10.19781/j.issn.1673-9140.2024.05.018
                    
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                        YANG Shuai1,2YANG Shuai
Power Supply Service Center, State Grid Hunan Electric Power Co., Ltd., Changsha 410004, China;Hunan Province Key Laboratory of Intelligent Electrical Measurement and Application Technology, Changsha 410004, China
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ZENG Wenwei1,2ZENG Wenwei
Power Supply Service Center, State Grid Hunan Electric Power Co., Ltd., Changsha 410004, China;Hunan Province Key Laboratory of Intelligent Electrical Measurement and Application Technology, Changsha 410004, China
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YANG Lingyun3YANG Lingyun
State Grid Hunan Electric Power Co., Ltd., Changsha 410004, China
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HUANG Rui1,2HUANG Rui
Power Supply Service Center, State Grid Hunan Electric Power Co., Ltd., Changsha 410004, China;Hunan Province Key Laboratory of Intelligent Electrical Measurement and Application Technology, Changsha 410004, China
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LIU Mouhai1,2LIU Mouhai
Power Supply Service Center, State Grid Hunan Electric Power Co., Ltd., Changsha 410004, China;Hunan Province Key Laboratory of Intelligent Electrical Measurement and Application Technology, Changsha 410004, China
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YI Qinyi4YI Qinyi
College of Electrical and Information Engineering, Hunan University, Changsha 410082, China
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GAO Yunpeng4GAO Yunpeng
College of Electrical and Information Engineering, Hunan University, Changsha 410082, China
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Affiliation:(1. Power Supply Service Center, State Grid Hunan Electric Power Co., Ltd., Changsha 410004, China;2. Hunan Province Key Laboratory of Intelligent Electrical Measurement and Application Technology, Changsha 410004, China;3. State Grid Hunan Electric Power Co., Ltd., Changsha 410004, China;4. College of Electrical and Information Engineering, Hunan University, Changsha 410082, China)
Clc Number:TM615
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Abstract:

The output power of photovoltaic (PV) arrays exhibits strong randomness and volatility. In the event of a fault, it can severely impact the safety and stable operation of the power system. Addressing the challenges of low accuracy and slow convergence in current PV fault diagnosis, this paper proposes a PV array fault diagnosis method based on the grasshopper optimization algorithm-support vector machine (GOA-SVM) model. Firstly, an equivalent circuit model of the PV array is established to analyze the variation characteristics of the PV array's voltage-current curve. Secondly, considering environmental factors and the nonlinear changes in the scale of the PV array, feature quantities reflecting different fault characteristics are extracted, and the data is mapped into a high-dimensional space for nonlinear processing. Finally, an improved method for optimizing the nonlinear support vector machine using GOA is proposed, and a GOA-SVM PV array fault diagnosis model is established, with simulations conducted using practical examples. The research results indicate that this method can be applied to various PV array models of different scales and effectively diagnose faults in PV arrays. For a 4×3 PV array scale, the data simulation classification accuracy can reach 99.8088%. When validated using the publicly available dataset from the national institute of standards and technology (NIST), the fault diagnosis accuracy achieves 92.3682%. Compared with other methods, this approach demonstrates significant improvements in recall rate and F1-Score.

Key words:photovoltaic array; fault diagnosis; multi-classification; optimal hyperplane; GOA-SVM mode

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杨帅,曾文伟,杨凌云,黄瑞,刘谋海,易钦逸,高云鹏.基于GOA‑SVM的光伏阵列故障诊断方法研究[J].电力科学与技术学报英文版,2024,39(5):172-180. YANG Shuai, ZENG Wenwei, YANG Lingyun, HUANG Rui, LIU Mouhai, YI Qinyi, GAO Yunpeng. Research on fault diagnosis method for photovoltaic array based on GOA-SVM[J]. Journal of Electric Power Science and Technology,2024,39(5):172-180.

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Online: December 02,2024
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