Research on evolutionary algorithms for multi-objective optimal operation of cascade reservoirs

In practical projects, the large-scale multi-objective optimization problems, represented by multi-objective optimal operation of cascade reservoirs,are difficult to be solved by general methods. Therefore, this paper proposes a new multi-objective particle swarm optimization (LMPSO),which includes both a fitness assignment approach based on the hypervolume indicator Ihk and a strategy to reduce search space dimensions based on problem transformation, in order to effectively deal with high-dimensional objective vectors and large-scale decision variables. The algorithm is applied to the medium-and-long-term multi-objective optimal operation of Xiluodu-Xiangjiaba cascade reservoirs, and the calculation results are comparatively analyzed with four established algorithms, to verify the excellent performance of LMPSO. It provides not only a reliable method to obtain high-quality Pareto solution sets in multi-objective optimal operation but also strong data support for the subsequent multi-objective operation decision-making. © 2020, China Water Power Press. All right reserved.