Discrete evolutionary programming for network splitting strategy: Different mutation technique

Abstract

Network splitting is performed to prevent the power system network from blackout event during severe cascading failures. This action will split the power system network into few islands by disconnecting the proper transmission lines. It is very important to select the optimal splitting solution (transmission lines to be removed) to ensure that the implementation of network splitting does not cause the system to worsen. Therefore, this paper investigates two different mutation techniques; single-level and three-level mutation, utilized in Discrete Evolutionary Programming (DEP) optimization to find the optimal splitting solution following a critical line outage. Initial cutsets based heuristic technique is employed to help the convergence of the DEP optimization with minimal power flow disruptions as its fitness function. The techniques are validated using the IEEE 30 and IEEE 118-bus system. The results show that three-level mutation technique produces better optimal splitting solution as compared to single mutation technique. © 2018 Institute of Advanced Engineering and Science All rights reserved.