Adaptability of Distribution Network Electrical Topology Identification Algorithm Based on Edge Computing

Abstract

With the rapid development of the national economy, the grid scale is continually expanding. The massive data in the operation of the distribution network brings great challenges to the distribution network electrical topology identification (DNETI). Edge computing can effectively solve the problem of computing and storage pressure of the master station in the face of massive data, as well as the delay and security problems in the transmission process. For edge computing scenarios, this paper studies the electrical topology identification algorithm of the distribution network and proposes an improved KNN algorithm. The simulation results show that the identification accuracy of the algorithm is as high as 97%. For the improved KNN algorithm, this paper also designs an algorithm adaptability test to identify the adaptability of the algorithm to software and hardware environment requirements. The results show that the algorithm has passed the software and hardware adaptability evaluation.