A multiobjective hybrid evolutionary algorithm for robust design of distribution networks

In this paper, an evolutionary multiobjective algorithm (NSGA-II) and some local search methods are employed to solve the power distribution network design problem. The design procedure takes into account three relevant aspects: monetary cost, fault cost (reliability) and robustness (ability to deal with different scenarios of load growth). The final objective is to identify topologies (conductor configuration and capacity) that are efficient with regard to cost and reliability at the same time they are robust enough for dealing with uncertainties on load prediction. Uncertainties in the load growth, energy price and interest rate are considered. Four local search methods are proposed in order to improve solution robustness and reliability, taking into account a given set of possible scenarios. The proposed algorithm achieves high-quality solutions with low computational cost, outperforming the results achieved by former works that dealt with similar problem formulations. Results for 21, 100 and 300 bus systems are presented in order to illustrate the efficiency of the proposed method.