Three-phase Imbalance Governance Method for Distribution Network Based on Big Data Analysis

Abstract

The three-phase imbalance problem of low-voltage distribution network users is prominent. Based on the big data analysis of power consumption behavior of users, this paper proposes a phase sequence allocation method without additional commutation equipment. Only one commutation operation can reduce the three-phase imbalance in a long time scale. Firstly, based on FCM clustering algorithm, the user curves with similar electricity consumption habits are clustered to form a typical electricity consumption behavior database. Secondly, the typical electricity consumption behavior curve obtained by clustering is used to replace the actual electricity consumption curve of the users in the substation area. With the minimum average three-phase imbalance of the substation area as the optimization objective, the nonlinear integer optimization of the access phase sequence of the users in the substation area is carried out based on genetic algorithm, and the power consumption behavior curve of the users in the substation area is proposed Phase sequence optimization deployment scheme. Simulation and examples show that the proposed allocation method can effectively reduce the three-phase imbalance, reduce line loss and improve the power system stability without frequent exchange phase sequence and equipment investment.