知识推理技术在梯级水电站长期调度方案研究中的运用  

Case-based Reasoning (CBR) Technology Used in Mid-long Term Optimal Operation of Cascaded Hydropower Stations

作　　者：古家平[1] 贺玉彬 马光文[1] 黄炜斌[1] 

机构地区：[1]四川大学水利水电学院,成都610065 [2]国电大渡河流域水电开发有限公司,成都610041

出　　处：《中国农村水利水电》2013年第10期103-106,共4页China Rural Water and Hydropower

基　　金：国家重点基础研究发展计划("973"计划)资助项目(2013CB036406);国家科技支撑计划资金资助项目(2008BAB29B09);国家自然科学基金资助重点项目(50539140);美国能源基金会"中国可持续能源"基金资助项目(G-0610-08581)

摘　　要：针对梯级水电站群中长期调度中存在的问题,将知识推理(CBR)技术应用于梯级水电站群中长期调度管理与决策中,通过梯级水电站优化后的运行数据及历史调度信息获取水电站调度知识,并通过知识推理机制实现智能化决策,在保证求解质量的同时,实现快速决策。结合具体流域实例,对基于CBR技术的梯级水电站群中长期调度方案的编制进行仿真计算,结果表明,CBR技术所得调度方案合理、可行、实用。Aiming at the existing problems in the cascade hydropower stations＇generation scheduling, Case-based reasoning （CBR） has been used in the mid-long term scheduling management and decision making in this paper. It obtains the scheduling knowledge of hydropower stations through running data and historical scheduling information. And it makes intelligent decision through CBR, which shows the advantages of simplifying access to knowledge, improving the efficiency and quality of problem solving. Finally, taking the specific river basin for example, this paper calculates mid-long term optimal operation of cascaded hydropower stations based on CBR. A It shows the characteristics of rationality, feasibility and practicality by analyzing the effects of CBR.

关 键 词：知识推理(CBR) 梯级水电站 中长期调度 调度规则 

分 类 号：TV697.11[水利工程—水利水电工程]