摘要
针对梯级水库群优化调度的大系统多维多阶段优化决策问题提出改进的蚁群算法。为提高算法搜索效率采用新的信息素更新策略——Ant-proportion,综合考虑全局和局部信息。以漫湾—大朝山梯级水电站优化调度为例,计算结果表明,改进算法与基本蚁群算法相比具有更好的优化结果和收敛速度,与逐步优化法相比可靠有效。
An improved ant colony optimization algorithm is introduced to solve the cascaded hydropower optimized scheduling problem with high-dimensional, multi-stage, and nonlinear characters. The improved algorithm adopts a new phenomenon update strategy called Ant-proportion, which takes into account both global and local information, to improve the optimization quality. Thus, the improved algorithm can hold much higher stability and convergence speed and better quality than that of classical ant colony optimization algorithm. By applying the model to the Manwan-Dachaoshan cascaded hydropower stations＇ operation problem, it reveals the improved algorithm has higher convergence speed and better quality than the classical. Comparing with the progressive optimality algorithm, it has been demonstrated that the improved algorithm is an effective alternative for cascaded hydroelectric optimal scheduling.
出处
《水电能源科学》
2008年第4期53-55,204,共4页
Water Resources and Power
基金
国家自然科学基金资助项目(50479055)
中国科学院知识创新工程青年人才领域前沿基金资助项目(07l4071d30)
