黄河上游水库群多目标优化调度研究
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摘要
为了使黄河上游梯级水库群在丰、平、枯水年的实际调度中最大限度地发挥效益,建立黄河上游水库群的多目标优化调度模型,选择1989—2008年共20 a的实测径流长系列资料,利用改进的快速非劣排序遗传算法(NSGA-Ⅱ)对模型进行求解。从水库发电、运行情况、供水满足度、防凌、生态等方面对模型计算结果进行分析,结果表明:在充分满足防凌和生态前提下,模型优化后的整个梯级水库群总发电量比"实际"发电量提高了2.07%、总缺水率平方和比实际降低了5.98%。
In order to maximize the benefit of the reservoir group of the Upper Yellow River in the actual scheduling years of wet,normal and dry years,the multi-objective optimization model was established. This paper selected a long-term actual runoff series from 1989 to 2008 as the study period,and used the improved Non-Dominated Sorting Genetic Algorithm-Ⅱ( NSGA-Ⅱ) method to solve the model. The model results were analyzed from several ways including reservoir power generation,operation situation,water supply satisfaction,preventing ice jam and ecological flow. The results show that the power generation of the whole cascade reservoir is 2.07%,which is higher than that of the actual power generation,and the total water shortage rate sum of squares is 5.98%,which is lower than that of the actual water shortage rate,under the precondition of fully satisfying the protection and the ecological environment.
In order to maximize the benefit of the reservoir group of the Upper Yellow River in the actual scheduling years of wet,normal and dry years,the multi-objective optimization model was established. This paper selected a long-term actual runoff series from 1989 to 2008 as the study period,and used the improved Non-Dominated Sorting Genetic Algorithm-Ⅱ( NSGA-Ⅱ) method to solve the model. The model results were analyzed from several ways including reservoir power generation,operation situation,water supply satisfaction,preventing ice jam and ecological flow. The results show that the power generation of the whole cascade reservoir is 2.07%,which is higher than that of the actual power generation,and the total water shortage rate sum of squares is 5.98%,which is lower than that of the actual water shortage rate,under the precondition of fully satisfying the protection and the ecological environment.
引文
[1]徐磊.基于遗传算法的多目标优化问题的研究与应用[D].长沙:中南大学,2007:1-7.
[2]董增川.水资源规划与管理[M].北京:中国水利水电出版社,2008:82-84.
[3]王方勇,袁吉栋,李静,等.基于河流健康的水库和谐调度模型研究[J].人民黄河,2010,32(6):7-9.
[4] DEB K,AGRAWAL S,PRATAP A,et al. A Fast Elitist Non-Dominated Sorting Genetic Algorithm for MultiObjective Optimization:NSGA-Ⅱ[J]. Lecture Notes in Computer Science,2000,1917:849-858.
[5]王学斌,畅建霞,孟雪姣,等.基于改进NSGA-Ⅱ的黄河下游水库多目标调度研究[J].水利学报,2017,48(2):135-156.
[6]董增川.水资源系统分析[M].北京:中国水利水电出版社,2008:178.
[2]董增川.水资源规划与管理[M].北京:中国水利水电出版社,2008:82-84.
[3]王方勇,袁吉栋,李静,等.基于河流健康的水库和谐调度模型研究[J].人民黄河,2010,32(6):7-9.
[4] DEB K,AGRAWAL S,PRATAP A,et al. A Fast Elitist Non-Dominated Sorting Genetic Algorithm for MultiObjective Optimization:NSGA-Ⅱ[J]. Lecture Notes in Computer Science,2000,1917:849-858.
[5]王学斌,畅建霞,孟雪姣,等.基于改进NSGA-Ⅱ的黄河下游水库多目标调度研究[J].水利学报,2017,48(2):135-156.
[6]董增川.水资源系统分析[M].北京:中国水利水电出版社,2008:178.