基于改进蚁群算法的雅砻江流域梯级联合优化调度研究

Research on Yalong River's Long-term Scheduling Based on Improved Ant Colony Optimization Algorithm

为了求解梯级水库群优化调度问题,提出一种改进蚁群算法(IACO,Improved ant colony optimization algorithm)。算法的改进主要包括嵌入邻域搜索和禁忌搜索,初始解生成技术和基于可行性的目标函数比较规则。以雅砻江流域梯级5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。

This paper proposes an improved ant colony optimization algorithm （IACO） to solve cascade hydro scheduling problem. In the proposed method, the improvements mainly includes three aspects. Firstly, the neighborhood search and taboo search is embed- ded in IACO. Secondly, the generation technology of initial solution is adopted in IACO. Thirdly, a feasibility-based selection compar- ison technique is devised to handle constraints effectively in 1ACO. The feasibility and effectiveness of the proposed IACO method are demonstrated for optimal generation scheduling of Yalong River＇s hydro system and the test results are compared with ACO in terms of solution quality and convergence property. The simulation results show that the proposed method is able to obtain good solution.