A new hybrid algorithm for the distribution system expansion planning problem

This paper presents a new hybrid optimization algorithm for the distribution expansion planning problem including distributed generation (DG). The proposed algorithm (BPSGA) combines the feature of two powerful algorithms: binary particle swarm (BPS) and the genetic algorithms (GAs). The objective of this work is to focus on the development of optimization algorithm to find the optimum scenario for the expansion of distribution system including DG as an alternative solution in addition to the expansion of existing substation and feeders. The resulted solution will satisfy operational and economical requirements by using DG as a candidate alternative for distribution expansion and reducing expanding existing substations and upgrading existing feeders. The model decides the locations and the size of the new facilities in the system as well as the amount of the purchased energy from the main grid. The results show that the proposed algorithm achieves better results than the previous algorithms.