| 引用本文: | 刘 凯,李镇海,吕 利,罗 文.基于聚类分析的配电台区拓扑识别方法[J].电力系统保护与控制,2022,50(6):165-171.[点击复制] |
| LIU Kai,LI Zhenhai,Lü Li,LUO Wen.Topology identification method for distribution areas based on clustering analysis[J].Power System Protection and Control,2022,50(6):165-171[点击复制] |
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| 摘要: |
| 拓扑识别是配电台区的技术热点之一，拓扑关系是电网普遍需求。在不额外增加拓扑识别硬件的条件下，利用台区同期电能数据进行拓扑识别，是有别于专用拓扑装置的另一种方法。研究了基于基尔霍夫定律的智能装置父子关系的特征条件和数学组合算法，并研究了基于聚类分析的拓扑识别算法，实现了从台区总出线开关到用户电能表的拓扑识别过程。提出了智能装置拓扑关系的主要数据结构和拓扑数据表单。基于聚类分析的机器学习方法和组合优化算法的拓扑识别技术，对于配电台区的运行和维护具有实用价值，对于配电数据孪生应用具有参考作用。 |
| 关键词: 配电台区 智能装置 聚类组合 拓扑识别 |
| DOI：DOI: 10.19783/j.cnki.pspc.210474 |
| 投稿时间：2021-04-23修订日期：2021-06-29 |
| 基金项目:江西省科技项目资助(S2020ZPYFB1256) |
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| Topology identification method for distribution areas based on clustering analysis |
| LIU Kai,LI Zhenhai,LÜ Li,LUO Wen |
| (1. Beijing Electrotechnical Society, Beijing 100193, China;
2. Jiangxi ENACS Renewable Energy and Micro Grid Innovations Co., Ltd., Ji’an 343100, China) |
| Abstract: |
| Topology identification is one of the hot topics of distribution area technology. Topology relation is a universal demand of a power grid. Using the same period energy data of the distribution area to do topology identification is another method and is different from the special topology device and has no additional hardware of topology identification. The characteristic conditions and mathematical combination algorithm of the parent-child relationship of intelligent devices based on Kirchhoff's theorem are studied, and a topology identification algorithm based on cluster analysis is studied. Then the topology identification process from the main switch of a distribution area to the user's electricity meter is realized. The primary data structure and topological data form of intelligent device topology relation are presented. The topology identification technology based on machine learning methods such as cluster analysis and combinatorial optimization algorithm has practical value for the operation and maintenance of a distribution station, and can be used as a reference for the twinning application of distribution data.
This work is supported by the Science and Technology Project of Jiangxi Province (No. S2020ZPYFB1256) |
| Key words: distribution area intelligent device clustering & combination topology identification |
