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，集中优化无法考虑单个利益联盟调度决策时的利益倾向。对此，建立了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。该博弈为主从博弈，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。在基于该主从博弈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模型。最终构成了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 used in optimal dispatching of wind-solar-hydro-thermal power including cascade hydropower. However, the upstream and downstream areas of cascade hydropower often belong to different interest alliances, and centralized optimization cannot consider the interest tendencies of a single interest alliance when making dispatch decisions. In this regard, a game optimization dispatch model with the goal of maximizing the respective interests of the upstream and downstream regions was established. The downstream provides a certain proportion of the downstream revenue increase to the upstream as compensation, and the upstream changes the scheduling strategy to increase the downstream revenue. This game is a Stackelberg game. The leader is the downstream that provides compensation and formulates the compensation coefficient, and the follower is the upstream that formulates the upstream scheduling strategy. In the double-layer nested optimization model based on this Stackelberg game, the upstream optimal scheduling model as the lower layer considers the downstream optimal scheduling strategy, that is, the lower-layer model is also a double-layer optimization model. Finally, a game optimization scheduling model based on the three-layer optimization model is formed. The results show that this model can promote the improvement of the overall benefits of both parties while ensuring the respective interests of the upstream and downstream regions.