Short-term distribution network expansion planning considering load and price uncertainties

Distribution Network Expansion Planning (DNEP) is the most important factor in the demand growth in the distribution system. Planning involves the best installation of new facilities such as allocation of new feeders, new substations, new routes of new feeders to substations and tie-line routes to other feeders. The Monte Carlo Simulation (MCS) is used for this purpose. In this paper, a new modification method is proposed under load and price uncertainties to obtain the best expansion scheme considering different candidate. Load duration curve is used to change annual load changes status. The objective function of proposed model is minimization of the total investment, operation and maintenance, line loss and reliability costs. Moreover, it is investigated voltage profile improvement and reduction of power losses during planning horizon. The proposed planning structure is optimized by using the Binary Particle Swarm Optimization (BPSO) technique. Finally the proposed method is evaluated on test network and simulation results prove the ability and effectiveness of the proposed planning method to deal with uncertainty and operating investment process.