The improvement of reservoir operation optimization (ROO) can lead to comprehensive economic benefits as well as sustainable development of water resources. To achieve this goal, an algorithm named wind-driven optimization (WDO) is first employed for ROO in this paper. An improved WDO(IWDO) is developed by using a dynamic adaptive random mutation mechanism, which can avoid the algorithm stagnation at local optima. Moreover, an adaptive search space reduction (ASSR) strategy that aims at improving the search efficiency of all evolutionary algorithms is proposed. The application results of the Goupitan hydropower station show that IWDO is an effective and viable algorithm for ROO and is capable of obtaining greater power generation compared to the classic WDO. Moreover, it is shown that the ASSR strategy can improve the search efficiency and the quality of scheduling results when coupled with various optimization algorithms such as IWDO, WDO and particle swarm optimization.

水库运行优化（ROO）的提高可以带来综合经济效益和水资源的可持续发展。为了实现这一目标，本文首先将一种名为风驱动优化（WDO）的算法用于 ROO。利用动态自适应随机变异机制开发了一种改进的WDO(IWDO)，避免了算法在局部最优处的停滞。此外，提出了一种旨在提高所有进化算法搜索效率的自适应搜索空间缩减（ASSR）策略。沟皮滩水电站的应用结果表明，IWDO 是一种有效可行的 ROO 算法，与经典 WDO 相比，能够获得更大的发电量。而且，