首页 | 本学科首页   官方微博 | 高级检索  
     

基于改进多目标粒子群算法的南水北调东线江苏段工程联合优化调度研究
引用本文:闻 昕,王 志,方国华,郭玉雪,周 磊.基于改进多目标粒子群算法的南水北调东线江苏段工程联合优化调度研究[J].水资源与水工程学报,2017,28(3):110-116.
作者姓名:闻 昕  王 志  方国华  郭玉雪  周 磊
作者单位:1.河海大学 水利水电学院, 江苏 南京 210098; 2.中国水利水电科学研究院, 北京 100038;3.南水北调东线江苏水源有限责任公司, 江苏 南京 210029;4.华东勘测设计研究院有限公司, 浙江 杭州 311122
基金项目:国家自然科学基金项目(51609061); 江苏省研究生培养创新工程项目(2016B03257); 江苏省水利科技项目(2014012); 江苏高校优势学科建设工程项目
摘    要:针对南水北调东线江苏段工程优化调度问题,构建协调系统缺水量和抽江水量两目标的联合优化调度模型,研发基于改进多目标粒子群算法的模型求解方法,建立组合赋权-TOPISIS方法进行多属性决策方法,形成基于"两线-三湖-四水源-六区间"的水资源调配空间格局,提出以大型泵站工程为核心的骨干枢纽联合调度方案。在50%、75%和95%来水条件下,经优化调度后受水区缺水量与常规调度相比分别降低了10.2×10~8m~3、16.4×10~8m~3、7.1×10~8m~3,系统抽江水量分别减少了17.4×10~8m~3、14.8×10~8m~3和12.2×10~8m~3。该方案可有效提高供水保障水平,充分发挥三大湖泊的调蓄能力,降低系统运行成本,具有显著的社会、经济等综合效益。

关 键 词:多目标优化  改进多目标粒子群算法  TOPISIS决策  泵站群

Study on optimal operation of Jiangsu section of estern route of South-to-North Water Diversion Project based on improved multi-objective particle swarm optimization algorithm
WEN Xin,WANG Zhi,FANG Guohu,GUO Yuxue,ZHOU Lei.Study on optimal operation of Jiangsu section of estern route of South-to-North Water Diversion Project based on improved multi-objective particle swarm optimization algorithm[J].Journal of water resources and water engineering,2017,28(3):110-116.
Authors:WEN Xin  WANG Zhi  FANG Guohu  GUO Yuxue  ZHOU Lei
Abstract:This paper is to develop the joint optimization and dispatching model of the Jiangsu section of the east line of the South-to-North Water Diversion Project, to explore the multi-objective particle swarm optimization algorithm, and to propose the multi-attribute TOPSIS decision-making method and an optimal scheduling scheme based on the large pumping station projects. The results show that the optimal scheduling scheme can effectively improve the utilization efficiency of water resources, giving full play to the storage capacity of the three lakes and reduce the pumping cost. With the inflow of 50%, 75% and 95%, the water shortages were reduced by 1.02 billion m3, 1.64 billion m3, and 0.71 billion m3 respectively, compared with the conventional dispatching. The pumping amount of the system could be reduced by 1.74 billion m3, 1.48 billion m3 and 1.22 billion m3, respectively, which has significant social, economic and other comprehensive benefits.
Keywords:multi-objective optimization  extended multi-objective particle swarm optimization algorithm  TOPISIS decision  pumping station group
本文献已被 CNKI 等数据库收录!
点击此处可从《水资源与水工程学报》浏览原始摘要信息
点击此处可从《水资源与水工程学报》下载全文
设为首页 | 免责声明 | 关于勤云 | 加入收藏

Copyright©北京勤云科技发展有限公司  京ICP备09084417号