A genetic algorithm based approach to LV radial distribution feeder load reconfiguration

This paper presents a genetic algorithm (GA) based reconfiguration method for consumer loads connected to a low voltage (LV) radial distribution feeder to reduce phase imbalance. The problem was formulated as a multi-objective optimization problem considering kilowatt-hour (kWh) energy consumption of consumers connected to a distribution feeder. In addition, optimization objectives have been derived to ensure minimum phase imbalance at each consumer access points of the feeder. The optimal configuration for a test distribution feeder was analyzed with uniform load profiles and non-uniform load profiles for consumers connected to the feeder. It has shown that when consumer load profiles are uniform, the proposed reconfiguration method can maintain a balance three-phase distribution feeder throughout the day. However, with the non-uniform consumer load profiles it renders a significant phase imbalance during certain time periods. Therefore, when different consumer types are connected to the feeder it is essential to develop an additional criterion to obtain the best configuration to maintain phase balance in the distribution feeder