A unit commitment method of pumped storage in renewable energy system via a twofold particle swarm optimization algorithm

Abstract

Abstract The problem of unit commitment of pumped storage power stations (UCPS) is rarely discussed in existing works of multi-energy hybrid systems scheduling. It goes against accurately evaluating the operation performance and reliability of the pumped storage unit (PSU). This study proposes a co-optimization scheduling method for a Wind-Photovoltaic-Pumped storage system based on a twofold particle swarm optimization (TPSO). At the system layer, a standard PSO algorithm is used to optimize the output of the pumped storage plant (PSP). At the PSP layer, an improved discrete PSO based on three discrete variables is used to solve the UCPS problem. It uses the constraint patching and the micro-increment rate method, respectively, with detailed consideration of the constraints on PSP and the characteristics of the PSU. Finally, the results of a case study show that refined UCPS can reduce the regulation intensity indicators such as operating duration by more than 25%, with better consistency with the characteristics of units. This work could provide a guideline for improving the operation benefits and reliability of the PSP.