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Optimal Expansion Planning of Distribution System Capacity with Respect to Distributed Generations

Nowadays, distributed generation (DG) is a new option in the power systems to meet the electrical demand growth as well as conventional methods such as substation reinforcement and feeder replacement. This paper presents a new approach to solve single and multi-objective distribution system expansion planning problem including DG and conventional method simultaneously. Since this optimization problem has a nonlinear complex nature, classical mathematical method cannot guarantee to achieve the global optimum solution. So, to overcome this encumbrance, a heuristic evolutionary algorithm based on binary particle swarm optimization (PSO) is proposed. The objective functions of this optimization problem are total expansion cost, voltage deviation, and system losses. The model resolves decision variables as follows: location and size of the DG units, new transformers, and upgraded feeders. This paper proposes several non-dominated solutions, so the decision maker can choose the optimal solution based on the importance of the different objectives. The 9-bus and 30-bus distribution test systems are utilized to show the effectiveness of the proposed method.