| 引用本文: | 沙浩源,郭 涛,赵学华,等.基于空间矢量复合判断指标的变电站动力电缆漏电检测算法[J].电力系统保护与控制,2023,51(11):168-176. |
| SHA Haoyuan,GUO Tao,ZHAO Xuehua,et al.Leakage detection algorithm for long-section power cables in substations based ona composite judgment index of space vector[J].Power System Protection and Control,2023,51(11):168-176 |
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| 摘要: |
| 为提高变电站长段动力电缆漏电监测水平，提出了一种基于空间矢量复合判据的变电站长段动力电缆漏电检测算法。首先对现有方法中无法检测三相漏电故障的问题进行了分析。然后，引入空间矢量的概念，将剩余电流数据转换为空间矢量圆，提出了剩余电流差流、A相漏电流以及空间矢量圆半径变化率3个漏电状态判断指标。并建立了针对电缆不平衡漏电及三相漏电故障的类型判断机制，实现了对长段动力电缆漏电状态及类型的准确检测。最后，通过仿真及江苏电网某500 kV变电站实际数据对所提方法的有效性与优越性进行验证。结果表明，该方法能够准确实现对不平衡漏电故障、故障演变过程以及三相漏电故障的判断，丰富了电缆漏电故障的诊断信息，有效提高了对变电站漏电问题的分析处理效率。 |
| 关键词: 高压变电站 长段动力电缆 剩余电流 空间矢量 漏电类型 智能运维 |
| DOI：10.19783/j.cnki.pspc.221179 |
| 分类号: |
| 基金项目:国家重点研发计划项目资助(2018YFB1500800)；江苏省重点研发计划项目资助(BE2020027)；江苏省国际科技合作项目资助(BZ2021012) |
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| Leakage detection algorithm for long-section power cables in substations based ona composite judgment index of space vector |
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SHA Haoyuan1, GUO Tao1, ZHAO Xuehua1, HE Maohui1, DENG Kai1, ZHU Chao1, CHEN Hao2, LI Xuan3
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1. State Grid Jiangsu Electric Power Co., Ltd. EHV Branch Company, Nanjing 211102, China; 2. Nanjing Power Supply
Branch, State Grid Jiangsu Electric Power Co., Ltd., Nanjing 210019, China; 3. State Grid Jiangsu
Electric Power Co., Ltd. Research Institute, Nanjing 211103, China
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| Abstract: |
| To improve the monitoring level of long-section power cables in substations, this paper proposes a leakage detection algorithm for long-section power cables in substations based on a space vector composite criterion. First, the limitations of existing cable leakage monitoring methods that cannot detect three-phase leakage faults are analyzed. Then, the concept of space vector is introduced and the residual current data is converted to a space vector circle. Residual current differential current, A-phase leakage current and space vector circle radius change rate, are proposed. A type judgment mechanism is established for cable unbalanced leakage and three-phase leakage faults. This provides accurate detection of the leakage status and type of long-section power cables. Finally, the effectiveness and superiority of the proposed method are verified by simulation and actual data of a 500 kV substation in the Jiangsu power grid. The results show that the method can accurately detect unbalanced leakage faults, fault evolution and three-phase leakage faults, enrich the information of cable leakage faults, and effectively improve the analysis and processing efficiency of leakage problems in substations. |
| Key words: high voltage substation long-section power cable residual current space vector leakage type intelligent maintenance |
