Optimization of power system network topology reconstruction algorithm based on edge computing

This article examines the enhancement of power system network topology reconstruction algorithm using edge computing to increase intelligence and responsiveness of the power system. Through the implementation of an edge computing framework, the research assigns computing responsibilities to various edge nodes, which results in less strain on the main server and enhances the efficiency of reconstructing network topology. This paper uses genetic algorithm for multi-objective optimization, taking into account processing efficiency, resource allocation and fault response capabilities. Experimental results show that the optimization algorithm shows significant performance improvement on data sets of different sizes, with execution time reduced by more than 25%, and accuracy and fault response time improved. This achievement provides theoretical support and practical basis for the intelligent and efficient operation of power systems. In terms of data set diversity, algorithm optimization and resource management, this article provides a wide range of application prospects and development space for future research.