Urban distribution network planning and zoning design based on improved K-means clustering in low carbon background

Abstract

Aiming at the problem that the traditional algorithm is difficult to adapt to the chaotic planning of urban distribution network and the uneven distribution of load points, an improved K-means clustering algorithm based zoning planning method of urban distribution network is proposed. Firstly, considering the effect of the capacity margin on the partition, the weighted factor is introduced to improve the Euclidean distance. Secondly, considering the selection of power supply units according to the distribution characteristics of the substation, the distance between the cluster center and the substation is calculated. Finally, a distribution network zoning planning model with the maximum number of inter-station power supply units and the minimum total Euclidean distance of power distribution as the objective function is constructed. Finally, taking the transformation of a distribution network in Fujian Province as a practical engineering example, the results show that the average difference of load partition obtained by the improved K-means clustering algorithm is reduced by 34.35% compared with the traditional method.