基于低压智能开关的低压台区拓扑识别应用OA

To address the issues of increasing users in the transformer areas of low-voltage distribution network and inconsistencies between recorded and actual topological structures,a topology identification method for low-voltage trans-former areas based on intelligent switch power data and location information is proposed in this paper.First,the phase voltage imbalance rate is used to filter users with significantly different voltage sequences,and the Pearson and Spear-man correlation coefficients are used to calculate the voltage correlations between coupled users.Second,the coupled users are classified into transformer areas by integrating the geographic location information from the intelligent switch,and the correlation coefficient is used as a substitute for the Euclidean distance to implement K-means clustering for coupled users in both the single-and multi-transformer areas.Third,power balance verification is conducted to deter-mine the supply relationships between users and transformers and those among users,and the feeder structures within the same transformer area are further classified based on the average correlation coefficient.Finally,simulation experi-ments on both the single-and multi-transformer areas validate the effectiveness of the proposed method.Results demon-strate that this method can accurately identify the topological structures of low-voltage transformer areas,providing re-liable support for the planning and operation of distribution network.