Multi-objective BPSO algorithm for distribution system expansion planning including Distributed Generation

Distributed Generation (DG) is a new approach in the electricity industry to meet the electrical demand growth in a suitable manner. This paper presents a solution method for the distribution expansion planning problem including DG. The proposed algorithm is based on Binary Particle Swarm Optimization (BPSO). The aim of the model is to satisfy operational and economical requirements by using DG as a candidate alternative for distribution system planning and avoiding or at least reducing: expanding existing substations, and upgrading existing feeders. The model decides the locations and size of the new facilities in the system as well as the amount of the purchased power from the main grid. The Conventional Weighted Aggregation (CWA) method is used to solve the multi-objective optimization problem so that further objectives functions can be added. The results show that the DG's introduce economical and electrical benefits to the system including improved voltage profile, feeders loading and losses.