供水优化调度系统的研究与应用
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摘要
供水系统是城市基础建设的重要组成部分,它不仅直接关系到城市居民的生活质量、而且极大的影响城市的经济发展,对于社会的安全稳定也有着重要的作用。然而目前城市供水系统的不合理运行产生了较多的水资源浪费、管网漏水甚至爆管等等问题,严重影响着供水安全。本文以长沙市供水管网为依托,着重研究如何建立合理的给水管网优化模型并进行有效的求解。
时用水量的预测是优化调度的前提和基础。本文建立了时用水量预测的模型群,利用广义神经网络预测模型进行了时用水量的预测。模型群的建立有效提高了预测算法的运算速度和预测精度。
根据水力学相关知识,供水管网参数中的测压点压力是供水优化调度模型的水力约束条件,而水厂供水量是优化调度目标函数的参数变量。由于管网的复杂多样性,难以建立它们的机理模型,本文建立了基于BP神经网络的测压点宏观压力模型以及水厂供水量与水厂出口水压、管网总用水量之间的宏观模型,为供水优化调度奠定基础。
本文以水厂出口压力为决策变量,以水厂电耗最小为优化目标,以测压点压力为约束条件建立了供水一级优化调度模型。给出了模型求解的改进PSO算法,得到优化调度方案。
最后,本文初步设计开发了一个供水优化调度系统,对上述建模和优化调度算法加以实现。
Water supply was an important component of urban infrastructure,it was not only directly related to the quality of life of urban residents,but also had a great influence for the development of urban economy,not to mention social security and stability. However,recently irrationality of urban water supply had produced a mass of water wasting,pipeline leaks and so on, which made some rather serious production.This paper was to based on Changsha city's water supply networks,and made an emphasization about how to build a rational water supply model and made a efficiently solve.
Water consumption forecast of urban's water network was the precondition and foundation.This paper established a water consumption forecast model group,and use generalized neural network forecasting model to make a precondition of water eonsumption.The establishment of model group can efficiently improve computational speed and accuracy of forecasts of algorithmic.
According to relative hydralics knowledge,among water supply networks,pressure point was a contraints,and then waterworks water supply was objective function of the parameters of variables.Due to complex diversity of networks, establishing accurate modle was rather difficulty.This paper was based on BP neural network and macro model of waterworks water supply,and then laid a foundation of water optimization.paper was based on waterworks export pressure regarding as decision variables, regarding mini-consuming power of waterworks as optimization target, and constituting a water level optimal scheduling model with pressure point . This paper put forward a ameliorating PSO arithmetic, and got a optimal scheduling programme.
Finally,this paper designed a optimal scheduling of water supply system, and achieved above modeling and arithmetic.
时用水量的预测是优化调度的前提和基础。本文建立了时用水量预测的模型群,利用广义神经网络预测模型进行了时用水量的预测。模型群的建立有效提高了预测算法的运算速度和预测精度。
根据水力学相关知识,供水管网参数中的测压点压力是供水优化调度模型的水力约束条件,而水厂供水量是优化调度目标函数的参数变量。由于管网的复杂多样性,难以建立它们的机理模型,本文建立了基于BP神经网络的测压点宏观压力模型以及水厂供水量与水厂出口水压、管网总用水量之间的宏观模型,为供水优化调度奠定基础。
本文以水厂出口压力为决策变量,以水厂电耗最小为优化目标,以测压点压力为约束条件建立了供水一级优化调度模型。给出了模型求解的改进PSO算法,得到优化调度方案。
最后,本文初步设计开发了一个供水优化调度系统,对上述建模和优化调度算法加以实现。
Water supply was an important component of urban infrastructure,it was not only directly related to the quality of life of urban residents,but also had a great influence for the development of urban economy,not to mention social security and stability. However,recently irrationality of urban water supply had produced a mass of water wasting,pipeline leaks and so on, which made some rather serious production.This paper was to based on Changsha city's water supply networks,and made an emphasization about how to build a rational water supply model and made a efficiently solve.
Water consumption forecast of urban's water network was the precondition and foundation.This paper established a water consumption forecast model group,and use generalized neural network forecasting model to make a precondition of water eonsumption.The establishment of model group can efficiently improve computational speed and accuracy of forecasts of algorithmic.
According to relative hydralics knowledge,among water supply networks,pressure point was a contraints,and then waterworks water supply was objective function of the parameters of variables.Due to complex diversity of networks, establishing accurate modle was rather difficulty.This paper was based on BP neural network and macro model of waterworks water supply,and then laid a foundation of water optimization.paper was based on waterworks export pressure regarding as decision variables, regarding mini-consuming power of waterworks as optimization target, and constituting a water level optimal scheduling model with pressure point . This paper put forward a ameliorating PSO arithmetic, and got a optimal scheduling programme.
Finally,this paper designed a optimal scheduling of water supply system, and achieved above modeling and arithmetic.
引文
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[4]郑爽英.城市供水系统二级优化调度的宏观模型研究.四川联合大学学报,1997,11(2):60-68
[5]吕谋,张土乔,赵洪宾.大规模供水系统直接优化调度方法.水利学报,2001,(7):84-90
[6]郑大琼,王念慎,杨军.多源大型供水管网优化调度.水利学报,2003,2:1-13
[7]俞亭超.城市供水系统优化调度研究:[博士学位论文].浙江:浙江大学,2004
[8]丁胜祥,董增川,王德智,李大勇.城市供水库群分解协调模型研究.水力发电.2006,32(7):17-19
[9]袁志彬,张悦.我国城市水资源现状及可持续发展的水工业战略.水资源,2000(5):43-45
[10]M.G.辛,A.铁脱里.大系统的最优化及控制.北京:机械工业出版社,1983
[11]金菊良,丁晶.水资源系统工程.成都:四川科学技术出版社,2002
[12]叶秉如.水资源系统优化规划和调度.北京:中国水利水电出版社,2001
[13]冯尚友.水资源系统工程.武汉:湖北科学技术出版社,1990
[14]钟平安,深圳市水资源系统优化调度模型研究,河海大学学报,2003(6):616-620
[15]董增川,叶秉如.水电站库群优化调度的分解方法.河海大学学报,1990,18(6):70-78
[16]徐琦,张勇传,孔力等.改进遗传算法在梯级电站日优化运行中的应用.水电能源科学,2002,20(4):51-53
[17]付永锋,沈冰,李智录,等.基于自适应遗传算法的金盆水库优化调度研究,水电能源科学,2004,22(3):47-50
[18]王煦法,张显俊,曹先彬.一种基于免疫原理的遗传算法.小型微型计算机系统,1999,20(2):117-120
[19]Shenglian H,Meng N,Wancheng G.Problems in GAand Necessarity of Importing Immune Function.Proceedings of the 3rd World Congress on Intelligent Control and Automation,Hefei China,2000
[20]孟繁桢,胡云昌,徐慧.具有免疫体亲近性的遗传算法及其应用.天津大学学报,1997,30(5):624-630
[21]程泽,寇纪淞,卜冬梅.一种基于免疫思想的混合式遗传算法.天津理工学院学报,2001,17(4):16-19
[22]宋朝红,罗强,纪昌明.基于混合遗传算法的水库群优化调度研究.武汉大学学报,2003,36(4):28-31
[23]冯尚友.可持续水资源利用与管理导论.北京:科学出版社,2000
[24]董增川.城市水资源供需系统分析.河海大学,1997
[25]M.阿佛里耳.非线性规划-分析与方法.上海:上海科技出版社,1979
[26]冯尚友.水资源系统工程.武汉:湖北科学技术出版社,1991
[27]尤详瑜,谢新民,孙仕军,等.我国水资源配置模型研究现状与展望.中国水利水电科学研究院学报,2004,2(2):132-134
[28]LV Mou,ZHANG Tuqiao,ZHAO Hongbin.Direct optimal dispatch of large scale water supply system.Journal of Hydraulic Engineering,2001(7):84.
[29]俞亭超,张土乔,吕谋.基于SVM的管网状态估计模型.哈尔滨工业大学学报,2005,37(9):1205
[30]Dandy G C,Engelhardt M.Optimal scheduling of water pipere- placement using genetic algorithms.Journal of Water Resources Planning and Management,2001,127(4):214
[31]王小平,曹立明.遗传算法——理论、应用与软件实现.西安:西安交通大学出版社,2002
[32]康大臣,赵洪宾.现行给水系统运行控制的局限.给水排水,2000,26(4):70-72
[33]吕谋.大规模给水系统多目标混合直接优化调度:[博士学位论文].哈尔滨:哈尔滨建筑大学,1998
[34]B.Coulbeck.Computer application in distribution system operation[MJ.Research studies press,1988:43-60
[35]E.C.Sodowski.Computer-generated optimal pumping schedules.J.AWWA,1995,87(7):73-78
[36].Demoyer and L.Horowitz.A system approach to water distribution modeling and control[M].Lexington ooks,Lexington,mass.1975:143-145
[37]M.J.H.Sterling and B.Coulbeck. Optimization of water pumping costs by hierarchical methods. Proceeding institute of civil engineerings, 1975a(Part2),59(2):787-797
[38]M.Sabet and O.Helweg.Cost ei}ective operation of urban water supply system using dynamic programming.Water resource bu11,1985,21(1 ):75-81
[39]B.Coulbeck.Optimization of water networks. Trans.Institute of measurement and control. 1984,6(5):271-279
[40]L.Ormsbee, T.Walski. D.Chase and W.Sharp. Methodology for improving pump operation efficiency.Journal of water resource planning and management,ASCE, 1989,115(2): 148-164
[41]K.E.Lansey and K.Awumah.Optimal pump operations considering pump switches Journal of water resources planning and management, 1994,120(1): 17-3 5.
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