中文摘要：

针对水电站优化调度高维、非线性、多约束以及模型不易求解的特点，本文提出将群居蜘蛛优化算法应用于水电站优化调度。算法依据群居蜘蛛的协同机制全局寻优，能够避免早熟收敛和陷于局部最优值，获得最优的水库调度决策。结合具体实例并与动态规划、遗传算法的效能进行比较，结果表明该方法不仅寻优效果好，而且稳健性强，参数少、搜索效率高，是一种有效的水电站优化调度模型的求解方法，可在实际中推广应用。

英文摘要：

An optimal operation model for hydropower station is characterized by high-dimension, nonlinearity, multiple constraints, and difficult model solution. To surmount these problems, this paper presents a social spider optimization （SSO） algorithm to solve such models. This new algorithm searches the global optimum using the synergy mechanism of social spiders, so that it can avoid premature convergence and local-optimum trapping and obtain stable results for optimal decision on reservoir operation. Its performances in a case study are compared with those of the dynamic programming （DP） and genetic algorithm （GA）. The comparison shows that with a smaller number of parameters, it is superior in calculations and more robust and efficient in optimum searching. Therefore, the social spider optimization algorithm is an effective method for practical optimization ofhydropower station scheduling models.