Distribution system expansion planning incorporating distributed generation

Abstract

Expansion planning of distribution system is the most significant tool which deals with the continuous increasing load demand. The main motive of the expansion planning is the minimization of the investment and operation cost of distribution network equipment which considers the installation/reinforcement cost of the substation, feeders, and Distribution Generation. In this paper, price and load uncertainties are taken into expansion planning which gives the robust and reliable expansion planning. These uncertainties are molded as Normal Probability Distribution Function. By using Monte Carlo Simulation, uncertainties are added into planning. A 9 bus distribution network is used for a case study of expansion planning. This multistage dynamic expansion planning problem is resolved by the Quantum Particle Swarm Optimization. The proposed algorithm is paralleled with the standard Particle Swarm Optimization and results shows the superiority of proposed algorithm over PSO.