摘要
以赣江流域内已建成的大型控制性水库为研究对象,将赣江流域上游至下游用水区概化成7个主要用水区域,综合考虑各水库的运用目标、流域主要用水区域水量需求以及河道内生态流量的要求,以水库群总发电量最大、用水区域总缺水量最小和外洲控制站调度后流量与天然流量偏差最小为目标,建立面向发电、供水、生态要求的赣江流域水库群优化调度模型,采用多目标粒子群算法进行求解,得到不同来水频率下发电、供水和生态3个目标的非劣解集,并对3个目标之间的竞争关系进行了剖析。最后分析了各典型方案相应的水库水位过程和区域缺水情况。结果表明:各来水频率下,发电、供水、生态3个目标之间竞争程度有强有弱,其中发电目标与生态目标之间、供水目标与生态目标之间存在较强的竞争性,发电目标与供水目标之间则相对较弱。
Taking key reservoirs in the Ganjiang River basin as the research object, seven main water useregions were generalized in the basin to develop a multi-objective optimal operation model oriented to thedemands of power generation, water supply and ecology. The operation model was designed to maximizepower generation of the reservoir group, minimize total water deficit of the water region while minimizingflow alteration of Waizhou Station, taking account of different objectives of reservoirs, the water demand ofmain regions and the requirements of the ecological instream flow. The multi-objective particle swam optimi-zation method was adopted in solving this model to obtain the non-dominated solution set of the three ob-jectives under different inflow frequencies, and the competition relationships among them were investigated.Then the corresponding water level process and water shortage situation of typical schemes were analyzed.The results indicate that the degrees of competition relationships among the three objectives are different.The competition between power generation and ecology, and that between water supply and ecology arefiercer,and the one between water generation and water supply is weaker.
作者
陈悦云
梅亚东
蔡昊
许新发
CHEN Yueyun;MEI Yadong;CAI Hao;XU Xinfa(Wuhan University, State Key Laboratory of Water Resources and Hydropower Engineering Science, Wuhan 430072, China;Jiangxi Provincial Institute of Water Sciences, Nanchang 330029, China)
出处
《水利学报》
EI
CSCD
北大核心
2018年第5期628-638,共11页
Journal of Hydraulic Engineering
基金
国家自然科学基金项目(51479140)
国家重点研发计划课题(2016YFC0401306)
关键词
发电
供水
生态
非劣解集
多目标粒子群算法
power generation
water supply
ecology
non-dominated solution set
muhi-objeetive particle swarm optimization