| 引用本文: | 杨晨曦,马 杰,杨 威,等.基于馈线负荷骤降度的配电网故障研判方法[J].电力系统保护与控制,2022,50(2):144-151.[点击复制] |
| YANG Chenxi,MA Jie,YANG Wei,et al.Distribution network fault location method based on the sudden drop ratio of feeder active load[J].Power System Protection and Control,2022,50(2):144-151[点击复制] |
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| 摘要: |
| 针对自动化水平低的配电线路故障停电后难以准确快速定位故障区段和停电范围的问题，提出了一种基于馈线负荷骤降度的配电网故障研判方法。该方法在馈线首端有功功率的骤降度大于一定阈值时启动，然后利用计量自动化系统中配变的历史负荷数据预测故障前馈线上各配变的有功功率，并计算馈线上各开关的负荷占比。通过比较馈线负荷骤降度与各开关负荷占比值，判断故障跳闸开关及停电范围。工程实例的分析结果表明，该方法能够准确定位故障跳闸开关，实时性好，为配电网提供了一种不依赖配电网自动化系统的新的故障研判手段。 |
| 关键词: 配电网 故障定位 故障研判 负荷预测 相似日 相关分析 |
| DOI：DOI: 10.19783/j.cnki.pspc.210361 |
| 投稿时间：2021-04-06修订日期：2021-05-14 |
| 基金项目:云南电网有限责任公司科技项目资助(YNKJXM 20191129，YNKJXM 20191176)；国家自然科学基金项目资助(51677060) |
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| Distribution network fault location method based on the sudden drop ratio of feeder active load |
| YANG Chenxi,MA Jie,YANG Wei,YANG Fanqi,YANG Xihang,HUANG Chun |
| (1. Kunming Power Supply Bureau, Yunnan Power Grid Co., Ltd., Kunming 650011, China;
2. College of Electrical and Information Engineering, Hunan University, Changsha 410082, China) |
| Abstract: |
| It is difficult to accurately and quickly locate the fault section and outage range after power failure in a distribution network with low-level automation. To solve this problem, a fault location and diagnosis method based on sudden drop ratio (SDR) of the feeder active load is proposed. After the feeder SDR exceeds a certain threshold, the active power of each distribution transformer on the faulty feeder is predicted using the historical load data in the metering automation system, and the load proportion of each switch is calculated. By comparing the feeder SDR and the power proportion of each switch, the fault trip switch and power failure range are judged. Analysis of the results of an engineering example show that the method can accurately locate the fault trip switch, and has good real-time performance. It provides a new fault diagnosis technique for a distribution network independent of the distribution network automation system.
This work is supported by the Science and Technology Project of Yunnan Power Grid Co., Ltd. (No. YNKJXM20191129 and No. YNKJXM20191176) and the National Natural Science Foundation of China (No. 51677060). |
| Key words: distribution network fault location fault analysis load forecasting similar days correlation analysis |
