集中优化被广泛应用于含梯级水电的风光水火优化调度,但梯级水电上下游区域往往属于不同利益联盟,导致集中优化无法考虑单个利益联盟调度决策时的利益倾向.为此,建立以上下游区域各自利益最大化为目标的博弈优化调度模型,下游向上游提供下游增收收益的一定比例作为补偿,上游更改调度策略使下游收益增收.作为主从博弈,其主体是提供补偿并制定补偿系数的下游,从体是制定上游调度策略的上游.在基于该构成的双层嵌套优化模型中,作为下层的上游优化调度模型考虑了下游的最优调度策略,即下层模型也为双层优化,最终构成基于三层优化模型的博弈优化调度模型.算例表明该模型能够在保证上下游区域各自利益的同时促进双方整体收益的提升.

Centralized optimization is widely applied in optimization scheduling of wind-solar-hydro-thermal power in cascade hydropower. However, upstream and downstream regions of cascade hydropower often belong to different interest alliances, which hinders centralized optimization from considering the individual preferences of each alliance in their scheduling decisions. To address this, a game optimization dispatch model is established with the goal of maximizing the interests for both upstream and downstream regions. The downstream region provides a certain proportion of its increased revenue as compensation to the upstream region, which adjusts the scheduling strategy to increase the downstream revenue. This game is modeled as a Stackelberg game, of which the leader is the downstream region that provides compensation and determines the compensation coefficient, and the follower is the upstream region that formulates its scheduling strategy. In the bi-level nested optimization model based on the Stackelberg game, the upstream optimal scheduling model at the lower level considers the downstream optimal scheduling strategy, namely, the lower-level model is also a bi-level optimization problem. Finally, a game optimization scheduling model is constructed based on the three-level optimization model. The results show that this model can ensure the individual interests for both upstream and downstream regions while promoting an overall increase in their combined benefits.