蚁群算法求解梯级电站短期优化调度改进研究

本文提出一种改进蚁群算法(Improved ant Colony Optimization Algorithm)求解梯级水库群短期优化调度问题。该算法的改进主要包括嵌入邻域搜索的单库轮换寻优、基于出力反推的初始解生成技术和约束优先的目标函数比较方法。以四川某中型流域梯级三级电站联合运行为背景,对蚁群算法和改进蚁群算法的求解质量和收敛性进行比较,实例验证表明,改进蚁群算法可以获得较好的优化调度结果。

Research on short-term optimized operation of cascade hydropower stations based on improved ant colony optimization algorithm

An improved ant colony optimization algorithm（IACO）is proposed herein to solve the problem from the short-term optimized operation of the cascade hydropower stations. The improvement of this algorithm mainly consists of embedding the single reservoir alternating optimization-searching for the neighborhood searching，the inverted deduction based generating technique for the initial solution and the comparison method for the objective function of constraint priority. By taking the joint-operation of the three cascade hydropower stations of a medium-sized basin in Sichuan Province as the study case，a comparison between both the ant colony optimization algorithm and its improved one is made for their solution qualities and convergence properties； from which it is demonstrated that a better optimized operation result can be obtain from the improved ant colony optimization algorithm.