MOSOA-Based Multiobjective Design of Power Distribution Systems

This paper presents a multiobjective (MO) evolutionary algorithm for solving a contingency-based MO design of power distribution system (PDS) by extending the original and powerful metaheuristic approach based on a MO seeker optimization algorithm (MOSOA). Normally, reliability is a major concern in existing PDS planning, as estimation of failure rates and fault repair duration of the feeder branches is difficult in practice. The proposed planning methodology uses a contingency-load-loss index for reliability evaluation, which is independent of the failure rate and fault repair duration of the feeder branches. This planning strategy includes distribution automation devices such as automatic reclosers (RAs) to enhance the reliability and efficiency of the distribution system. The proposed algorithm generates a set of nondominated solutions by the simultaneous optimization of two conflicting objectives (economic cost and overall system reliability) using Pareto-optimality-based tradeoff analysis. The performance of the proposed approach is assessed and illustrated on a 54-bus distribution system, considering real-time design practices and meeting the additional requirements that the designer imposes. The information gained from the Pareto-optimal solution is shown to be useful for final decision making of a PDS. Furthermore, a qualitative comparison is made with the nondominated sorting genetic algorithm-II, showing the efficacy of the proposed planning approach.