Abstract: From the lower reaches of the Jinsha River to the Three Gorges, a complex joint scheduling pattern comprising six reservoirs has emerged. This pattern is characterized by an expanded scope of scheduling, numerous and diverse constraints, and a range of optimization objectives. Consequently, formulating appropriate scheduling schemes has become particularly challenging. Recognizing the limitations of traditional particle swarm algorithms in addressing this scheduling model, we propose a multi-group gravitational particle swarm algorithm to enhance the optimization capabilities of the scheduling model. To this end, a multi-scale and multi-objective nested scheduling model is established, and the improved algorithm is applied to solve it. The test and application results demonstrate that the multi-group gravitational particle swarm algorithm exhibits superior optimization performance compared to other approaches. Moreover, it is more suitable for achieving optimal operation of cascade reservoirs. A case study further illustrates that the upstream leading power station can enhance the generation of downstream power stations and cascade stations by reducing its own power generation capacity.

Key words: optimal operation of reservior groups, particle swarm optimization, algorithm improvement, cascade reservoir, lower Jinsha River, Three Gorges