Big data technology based topology identification method of distribution station area

Abstract

Aiming at the problems of inaccurate distribution network topology relationship, complex lines and lack of accurate topology information records, this paper proposes a topology identification method based on big data technology. By collecting the information of switching current, power and current harmonics at all levels in the station area, the electrical parameter identification metabase is established, and the clustering analysis of the metabase is completed based on the improved k-means algorithm, according to the results of cluster analysis, the topological connection relationship of equipment in the station area is obtained. Through verification and analysis, the proposed method effectively improves the accuracy of topology identification of distribution station area, realizes the efficient and accurate identification of topology of low-voltage distribution station area, and provides an important foundation for the intelligent application of distribution network.