Optimal Feeder Reconfiguration of Power Distribution Network using PSO with Population Adaptation

This paper presents the distribution network optimal feeder reconfiguration problem, which is formulated using multi-objective functions such as voltage profile optimization, active power loss reduction, and load balancing. The formulated problem is solved using a technique incorporating Population Adaptation with Particle Swarm Optimization (PAPSO). In the proposed PAPSO technique, the concept of diversity is used to determine stagnation in the population. Thereafter, an enhancement step of population adaptation is employed to induce randomness in the particle population that reinitializes the population for further search. The outcomes are depicted on a modified IEEE 33-bus network at distribution voltage level, showing the most optimum feeder configuration obtained using the proposed algorithm. Furthermore, a quantitative comparison has been made between the PAPSO and standard Particle Swarm Optimization (PSO) results. The results and discussion depict that the suggested technique is relatively effective in providing the best solution in accordance with the set objectives.