Dynamic expansion planning of power distribution grids with distributed generation resources using a new two-level optimization algorithm

This paper presents a comprehensive model for dynamic expansion planning of distribution grids (DDGEP) considering distributed generation technologies. The proposed model determines the optimal location, capacity and dynamics (i.e. timing) of DG investment as well as optimal time schedule of reinforcement of distribution feeders. The objective function of this model encompasses both investment and operation costs of distribution grids and DG units along a specified planning horizon. To solve the suggested model, a new two-level solution method composed of Binary Enhanced Imperialist Competition Algorithm (BEICA) and Improved Particle Swarm Optimization (IPSO) is introduced. BEICA optimizes the location, capacity and timing of DG investment and also timing of existing feeder's reinforcement while IPSO optimizes the operation point of distributed generator-integrated distribution system. In order to demonstrate the effectiveness of proposed two-level solution approach (BEICA⃴), it is applied on a radial distribution test system and the obtained results are compared with several other solution methods.