Optimitization of Interconnection of Reclosers via Fiber Optic to the Automation of Energy Network with Self-Healing

Abstract

In this article, it is proposed the use of a multiobjective genetic algorithm NSGA-II (Nondominated Sorting Genetic Algorithm) for dimensioning the mesh optical network that connects the reclosers of a smart grid which has the self-healing capacity. Considering only link distances (cost), this dimensioning can be done considering the solution to the Traveling Salesman Problem. Thus, we first present in this work a performance comparison of the following algorithms used to solve the Traveling Salesman Problem (TSP): Brute Force, Cross Entropy, Genetic Algorithm, and Nondominated SortingGenetic Algorithm (NSGAII). Next, we propose the NSGA-II to dimension the mesh optical network, considering factors such as cost and throughput.

Keywords

• Genetic Algorithm
• Multi-objective Optimization
• Smart Grid
• Self-Healing
• Telecommunications