Multi‐objective planning model for multi‐phase distribution system under uncertainty considering reconfiguration

In this study, multi-objective particle swarm optimisation (MOPSO) and preference order (PO) ranking-based multi-objective planning model is presented for placement and sizing of wind and solar-based distributed generators (DGs), and capacitors in the multi-phase distribution network, under uncertainty considering network reconfiguration. Uncertainty in solar irradiance, wind speed, and load are considered using Monte Carlo simulation (MCS) with suitable probabilistic models. The planning problem is formulated considering different scenarios generated using MCS. For objective function formulation with varying demand and generation conditions, a dynamic load generation model is developed. A priority vector is proposed for DG and capacitor placement using the analytic hierarchy process to reduce the search space and computational time. The key benefits of the proposed DG placement algorithm are that it gives a single solution that is nearly optimal for all the possible network topologies and it works well for both unbalanced and balanced conditions. The proposed technique has been applied to IEEE 34-bus and IEEE 123-bus systems. The result shows a significant reduction in power losses, current unbalancing and improvement in reliability after the placement of DGs and capacitors.