Meta-heuristic approach for Distributed Generation planning in electricity market paradigm

Renewable Distributed Generations (DGs), are being increasingly placed in the power system networks due to their several technical, economical and environmental benefits. In this paper, a heuristic approach utilizing Modified Particle Swarm Optimization method is considered for placement of DGs. Monte Carlo Simulation (MCS) based probabilistic load flow, considering uncertainty in load demand and generation, is used to find unavailability of wind generation, under no wind and/or over voltage conditions. The Net Present Value (NPV) analysis of the optimal DG planning under electricity market paradigm is carried out for biomass DG, wind DG and Solar Photo Voltaic (SPV) DG for their ranking. The proposed market-based analysis is simple and generic, and provides choice to the distribution company to choose DGs under various constraints. Results on two practical distribution networks demonstrate the effectiveness of the proposed method.