A case study on optimizing an electrical distribution network using a genetic algorithm

This paper presents an evolutionary approach for optimizing the topology of rural electrical distribution networks. The primary objective of this project is to determine if the rural distribution network for a case study has expanded in an optimal manner through finding the shortest weighted path between network customers, thereby establishing the cost. Currently, there are large portions of the distribution network assets in rural areas that are nearing end of life and will need to be replaced in the near future. This presents the opportunity to redesign the routing of the network through the consideration of all customers, with the expectation that the length of the network and thus the level of investment will be reduced. The minimum spanning tree (MST) and genetic algorithm (GA) are used to compute the optimized path throughout a constraint weighted area. The results indicate that the optimized path of the network produces a considerable reduction in the total cost.