Distributed Economic Dispatch for Multi-area Power Systems Based on Multi-objective Differential Evolution Algorithm

Economic dispatch of a multi-area interconnected power system with wind, solar, and energy storage units is a typical non-convex and nonlinear optimization problem, which is difficult to be solved by the existing mathematical programming methods. In this paper, a distributed multi-objective differential evolution algorithm is proposed. Firstly, to improve the global search ability of the multi-objective differential evolutionary algorithm, the population is partitioned using a competitive mechanism. A multi-strategy scheme is used according to the partition to enhance the diversity of the algorithm. Secondly, the IEEE 39-bus system is decomposed into several sub-areas using the bus tearing method and the interval information is transmitted through the boundary tie-lines. Then a distributed method is proposed to be applied to the above algorithm, where each sub-algorithm solves the sub-problem associated with each area. Finally, the IEEE 39-bus system is divided into two-area and three-area interconnected systems, and the performance of the algorithm is verified on the modified IEEE 39-bus system. The experimental results verify the effectiveness of the improved multi-objective differential evolution optimization algorithm and the feasibility of the distributed approach.