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考虑信号畸变的多源信息融合配电网故障定位方法

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准确定位配电网故障区段,对提升供电服务满意度、优化营商环境具有重要意义.目前基于低压侧用户停电信息的多源信息融合配电网故障定位方法在馈线自动化终端(feeder terminal unit,FTU)信号发生畸变时,依然会出现误判,特别是在低压侧用户停电信息采集失败时,故障定位准确率大大降低.文章在现有模型基础上引入 FTU 开关跳闸(变位)信号,校正模型输入,构建了一个高容错度的配电网故障定位模型.通过算例仿真分析,证明了该方法在单一故障信号畸变和停电信息采集失败 2 种场景下相较于未考虑信号校正的方法具有更高的准确性.
Multi-source Information Fusion Fault Localization Method for Distribution Network Considering Signal Distortion
Accurately locating the fault section of the distribution network can have significant implications for improving power supply service satisfaction and optimizing the business environment.At present,the multi-source information fusion distribution network fault location method based on the low-voltage user outage information will still misjudge when the signal of the automated feeder terminal unit(FTU)is distorted,especially when the low-voltage user outage information collection fails,the fault location accuracy is greatly reduced.This paper introduces a FTU switch trip signal to adjust the model input based on the existing framework,ultimately constructing a fault location model with enhanced fault tolerance.The simulation results show that the proposed method has higher accuracy than the method without signal correction when the single fault signal is distorted or the fault information of low-voltage users cannot be collected.

distribution networkfault locationsignal distortion correctiondistribution automationgenetic algorithm

袁哲、孙明辉、颜伟

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国网重庆市电力公司 璧山供电分公司,重庆市 璧山区 402700

无锡中微高科电子有限公司,江苏省 无锡市 214000

南京师范大学 电气与自动化工程学院,江苏省 南京市 210000

配电网 故障定位 信号畸变校正 配电自动化 遗传算法

国家自然科学基金项目安徽省科技重大专项项目

52107005202203a05020023

2024

电力信息与通信技术
中国电力科学研究院

电力信息与通信技术

CSTPCD
影响因子:0.699
ISSN:1672-4844
年,卷(期):2024.22(10)
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