混合式蓄能水电站优化调度与风险分析方法及应用研究
|
摘要
改善电源结构,充分利用可再生能源,加快蓄能水电站建设,提高蓄能水电站的运行管理水平,对构建资源节约型和环境友好型社会及推动电力工业可持续发展具有重要作用。本文以混合式蓄能水电站为研究对象,从优化调度算法、风险分析方法、中长期优化调度、实时调度、调度风险分析和评价等不同角度深入探讨了电站的优化调度管理问题,并取得了如下主要成果：
(1)混合式蓄能水电站的优化调度是一个多阶段、非线性和组合性的问题,针对目前采用的基本粒子群算法在求解时存在易陷入局部最优和早熟的缺点,提出以随机动态改变惯性权重机制来选取惯性权重因子、以混沌变量生成机制增加粒子的多样性、以逐步优化和随机生成相结合增加粒子生成的有效性的改进粒子群算法(APSO)进行求解,为混合式蓄能水电站的优化调度提供了一种有效的方法。
(2)针对目前水库调度运行管理实际,基于事件与事件的目标,即事件发生的途径空间和目标空间是可变的思想,提出了概率最优化风险分析方法(POMR),深入地刻画出风险与效益的对立关系,为调度人员的决策提供了基础理论方法。
(3)针对发电量最大和调峰效益最大、上库和下库联合调度,存在着多维、多阶段和多约束条件等具有高度复杂性的问题,建立了混合式蓄能水电站中长期优化调度模型,并采用APSO求解。实例研究证明了所建模型的合理性和算法的有效性,所建模型对解决混合式蓄能水电站中长期优化调度运行管理问题具有重要的理论价值和广阔的应用前景。
(4)建立了基于调度函数的混合式蓄能水电站实时调度模型。把时间、空间和能量因子作为待选变量,提出用逐步回归原理建立混合式蓄能水电站的调度函数。在考虑电站自身发电、综合利用及电站出力等约束的基础上,采用调度函数对某混合式蓄能水电站进行实际运行模拟,并对模拟结果与优化调度结果进行了对比。结果表明调度函数基本保留了优化调度方案的成果和效益,同时具有良好的可操作性和解释性,为混合式蓄能水电站寻找调度规律、拟定运行方案提供了一种新的方法。
(5)在构建发电调度风险评价指标体系的基础上,运用不确定性理论和POMR方法建立了混合式蓄能水电站调度风险分析的期望值模型,并给出简便实用的求解方法。实例应用表明,该模型实现了水库在承担一定风险的情况下,可以追求电站效益的最大化,并通过灵敏度分析建立目标空间与因子空间的关系,达到通过控制风险因子改善较优可行方案的目的,对调度方案决策具有重要指导意义。
(6)针对围堰漫堰的主要风险因子,建立了基于POMR方法的围堰漫堰风险分析模型,并把此模型应用于向家坝水文站一期围堰漫堰风险计算。在对横江洪水特点和顶托分析的基础上,采用3层BP神经网络对向家坝水文站水位变化进行预测,探讨了汛期横江洪水入流对向家坝一期围堰河段水位的顶托影响,并建立了向家坝一期围堰漫堰风险模型,为管理决策人员提供了汛期围堰安全度汛的依据。
It is very important to improve the power source structure, make full use of renewable energy and enhance the operation and management level of pumped-storage power stations for constructing a resource-saving and environment-friendly society and sustainable development of power industry. The operation and management of mixed storage power station are further discussed by adopting different ways such as the optimal scheduling algorithm, risk analysis and evaluation, long-term optimal scheduling, real-time scheduling, etc. in this paper. The conclusions are as follows:
(1) In order to solve multi-stage, non-linear and other difficult problems of optimal operation of mixed storage power station, a novel and efficiency algorithm, Advanced Particle Swarm Optimization (APSO) is presented in the thesis. The mechanism of random dynamically changing inertia weight and the generation mechanism of chaotic variables are introduced to increase the diversity of particles which can avoid the local optimization and premature of the PSO algorithm.
(2) Based on events and their goals, in another way, the way space and target space can be changed when events have happened, Probability Optimization Method for the Risk Calculating (POMR) which discusses the antagonistic relationship between risks and benefits is proposed after analyzing the actual operation and management of reservoirs. And this antagonistic relationship is very important when dispatchers make the decision.
(3) The long-term optimal scheduling model of mixed storage power station is constructed to solve the complex problems, for instance, the Multi-constrained, multi-stage and non-linear in the joint reservoir operation and energy maximization.
(4) The real-time scheduling model of storage power station based on the scheduling function is founded. Time, space and energy factor are variables to be elected in this scheduling function which is design by using regression theory. Taking all the aspects into account, this paper compares the simulation results calculated by the scheduling function with the optimal scheduling results. The results show that the model based on the scheduling function can receive better plan and provide a new approach for the operation of mixed storage power station.
(5) In the base of risk evaluation index system for generation scheduling, expectations model for risk analysis of mixed storage power station is established by using the POMR methods and uncertainty theory, and simple and practical solution method is presented. The applications show that the model can pursue the maximal efficiency of power plant in a certain risk circumstances, and establish the relationship between target space and factor space through sensitivity analysis also can improve the operation by controlling the risk factors. So this model is significant for making the operation scheduling.
(6) Risk analysis model of cofferdam based on the POMR method which is adopted to solve the risk factors is proposed in this paper. It has been applied to calculate the risk in the first cofferdam of Xiangjiaba Hydrometric. After analysis the flood features and the backwater of hengjiang, three-layer BP neural network is used predict the water level of Xiangjiaba Hydrometric. Then the influence of the hengjiang inflow to the first cofferdam of Xiangjiaba also discussed. The risk model of the first cofferdam of Xiangjiaba is also established. This provids the basis for the flood season cofferdam security for managers decision-making.
(1)混合式蓄能水电站的优化调度是一个多阶段、非线性和组合性的问题,针对目前采用的基本粒子群算法在求解时存在易陷入局部最优和早熟的缺点,提出以随机动态改变惯性权重机制来选取惯性权重因子、以混沌变量生成机制增加粒子的多样性、以逐步优化和随机生成相结合增加粒子生成的有效性的改进粒子群算法(APSO)进行求解,为混合式蓄能水电站的优化调度提供了一种有效的方法。
(2)针对目前水库调度运行管理实际,基于事件与事件的目标,即事件发生的途径空间和目标空间是可变的思想,提出了概率最优化风险分析方法(POMR),深入地刻画出风险与效益的对立关系,为调度人员的决策提供了基础理论方法。
(3)针对发电量最大和调峰效益最大、上库和下库联合调度,存在着多维、多阶段和多约束条件等具有高度复杂性的问题,建立了混合式蓄能水电站中长期优化调度模型,并采用APSO求解。实例研究证明了所建模型的合理性和算法的有效性,所建模型对解决混合式蓄能水电站中长期优化调度运行管理问题具有重要的理论价值和广阔的应用前景。
(4)建立了基于调度函数的混合式蓄能水电站实时调度模型。把时间、空间和能量因子作为待选变量,提出用逐步回归原理建立混合式蓄能水电站的调度函数。在考虑电站自身发电、综合利用及电站出力等约束的基础上,采用调度函数对某混合式蓄能水电站进行实际运行模拟,并对模拟结果与优化调度结果进行了对比。结果表明调度函数基本保留了优化调度方案的成果和效益,同时具有良好的可操作性和解释性,为混合式蓄能水电站寻找调度规律、拟定运行方案提供了一种新的方法。
(5)在构建发电调度风险评价指标体系的基础上,运用不确定性理论和POMR方法建立了混合式蓄能水电站调度风险分析的期望值模型,并给出简便实用的求解方法。实例应用表明,该模型实现了水库在承担一定风险的情况下,可以追求电站效益的最大化,并通过灵敏度分析建立目标空间与因子空间的关系,达到通过控制风险因子改善较优可行方案的目的,对调度方案决策具有重要指导意义。
(6)针对围堰漫堰的主要风险因子,建立了基于POMR方法的围堰漫堰风险分析模型,并把此模型应用于向家坝水文站一期围堰漫堰风险计算。在对横江洪水特点和顶托分析的基础上,采用3层BP神经网络对向家坝水文站水位变化进行预测,探讨了汛期横江洪水入流对向家坝一期围堰河段水位的顶托影响,并建立了向家坝一期围堰漫堰风险模型,为管理决策人员提供了汛期围堰安全度汛的依据。
It is very important to improve the power source structure, make full use of renewable energy and enhance the operation and management level of pumped-storage power stations for constructing a resource-saving and environment-friendly society and sustainable development of power industry. The operation and management of mixed storage power station are further discussed by adopting different ways such as the optimal scheduling algorithm, risk analysis and evaluation, long-term optimal scheduling, real-time scheduling, etc. in this paper. The conclusions are as follows:
(1) In order to solve multi-stage, non-linear and other difficult problems of optimal operation of mixed storage power station, a novel and efficiency algorithm, Advanced Particle Swarm Optimization (APSO) is presented in the thesis. The mechanism of random dynamically changing inertia weight and the generation mechanism of chaotic variables are introduced to increase the diversity of particles which can avoid the local optimization and premature of the PSO algorithm.
(2) Based on events and their goals, in another way, the way space and target space can be changed when events have happened, Probability Optimization Method for the Risk Calculating (POMR) which discusses the antagonistic relationship between risks and benefits is proposed after analyzing the actual operation and management of reservoirs. And this antagonistic relationship is very important when dispatchers make the decision.
(3) The long-term optimal scheduling model of mixed storage power station is constructed to solve the complex problems, for instance, the Multi-constrained, multi-stage and non-linear in the joint reservoir operation and energy maximization.
(4) The real-time scheduling model of storage power station based on the scheduling function is founded. Time, space and energy factor are variables to be elected in this scheduling function which is design by using regression theory. Taking all the aspects into account, this paper compares the simulation results calculated by the scheduling function with the optimal scheduling results. The results show that the model based on the scheduling function can receive better plan and provide a new approach for the operation of mixed storage power station.
(5) In the base of risk evaluation index system for generation scheduling, expectations model for risk analysis of mixed storage power station is established by using the POMR methods and uncertainty theory, and simple and practical solution method is presented. The applications show that the model can pursue the maximal efficiency of power plant in a certain risk circumstances, and establish the relationship between target space and factor space through sensitivity analysis also can improve the operation by controlling the risk factors. So this model is significant for making the operation scheduling.
(6) Risk analysis model of cofferdam based on the POMR method which is adopted to solve the risk factors is proposed in this paper. It has been applied to calculate the risk in the first cofferdam of Xiangjiaba Hydrometric. After analysis the flood features and the backwater of hengjiang, three-layer BP neural network is used predict the water level of Xiangjiaba Hydrometric. Then the influence of the hengjiang inflow to the first cofferdam of Xiangjiaba also discussed. The risk model of the first cofferdam of Xiangjiaba is also established. This provids the basis for the flood season cofferdam security for managers decision-making.
引文
[1].张挺,张平.抽水蓄能电站的电量效益.水力发电,2009,(1)：14～17
[2].果瑞金.混合式抽水蓄能电站优化调度刍议.水利水电技术,1997,28(3)：44～46
[3].陆佑楣,潘家净.抽水蓄能电站.北京：水利电力出版社,1992.24-38
[4].周之豪,陈崇仁,王海曙.抽水蓄能电站建设的新发展.河海大学科技情报,1989,9(3)：1-8
[5]. International water power and dam construction 1997 year book. Wilmington Business Publshing,1997
[6].Cgeol MSc Dic FGS. Pumped storage part II:North Amarica Africa and Asia.International Wa-ter Power and Dam Construction.1995,47(7):34～36
[7]. Cheng Xuemin. Recent progress in pumped strage schemes in China.International Water Power and Dam Construction,1993,45(2):16～19
[8].唐文化,李小燕,李友起.潘家口抽水蓄能电站水能参数的设计.水力发电,1995,(8)：40～61
[9].陈文.响洪甸混合式抽水蓄能电站工程特点.水利水电技术,1996,(10)：14～53
[10].王平,冯庆华,邱玉怀.响洪甸混合式抽水蓄能工程的运行方式和综合效益.水利水电技术,2000,31(2)：11～13
[11]. J. D. C.Little. The use of storage water in a hydroelectric system, oper. Res,3,1995
[12]. Gagnon, C. R., R. H, Hicks, S. L. S. Jacoby, et al. A Nonlinear Programming Approach to a Very Large Hydroelectric System Optimization. Math. Program.1974.6:28～41,
[13]. Larson, R.E., State Incremental Dynamic Programming, Elsevier, New York,1968
[14].Trott, W.J, and W.W G..Yeh, Optimization of Multiple reservoir systems, J.Hhdraul. Div. Am. Soe. Civ. Eng.1983,99(Hy10):1865～1844
[15]. Giles. J. E, and W.O., Wunderlick, Weekly multipurpose planning model for TVA reservoir system, J. of the Water Resour, Plann. Manage.Div. Am. Soe. Civ. Eng.1981,107(WR2):495～511,
[16]. Murray, D. M. and S.J. Yakowitz, Constrained differential dynamic Progrmaming and its application to multireservoir control, Water Resour. Res.1979,15(5):1017-1027,
[17].TurgeonA., optimal short-term hydro scheduling from the principle of progressive optimality, Water Resour. Res.1981,17(3):481～486,
[18].Howson, H.R., and N.C.F. Saneho, A new algorithm for the solution of multistate dynamic programming problems, Math. Programm.1975,8(1):35～41
[19]. Arvanitidis, N.V, and J. Rosing, optimal Operation of multireservoir systems using a composite representation, IEEE Transactions on Power apparatus and systems,1970, 89(2)
[20].Heidari M, Chow V T, Kokotovie P V, et al.Diserete Differential Dynamic Programming Approach to Water Resources Systems Optimization.Water Resour. Res.,1971,7(2):155～164
[21]. Larson, R.E., State Incremental Dynamic Programming, Elsevier, New York,1968
[22].Trott, W.J, and W.W G.Yeh, Optimization of Multiple reservoir systems, J.Hhdraul. Div. Am. Soe. Civ. Eng.,1983,99(10):1865～1844,
[23]. Giles. J. E, and W.O., Wunderlick, Weekly multipurpose planning model for TVA reservoir system, J. of the Water Resour, Plann. Manage.Div. Am. Soe. Civ. Eng.1981,107(2):495～511,
[24]. Murray, D. M. and S.J. Yakowitz, Constrained differential dynamic Progrmaming and its application to multireservoir control, Water Resour. Res.1979,15(5):1017～1027,
[25].TurgeonA., optimal short-term hydro scheduling from the principle of progressive optimality, Water Resour. Res.1981,17(3):481～486,
[26].Howson, H.R., and N.C.F. Saneho, A new algorithm for the solution of multistate dynamic programming problems, Math. Programm.1975,8(1)
[27]. Marino, M.A., and B. Mohammadi, Reservoir operation by linear and dynamic programming, J. Water Resour. Plann. Manage.,1983,104(4):25～32
[28].Esat, V., and Hall, M. J.. Water Resources System Optimization Using Genetic Algorithms. Hydroinformatics'94, Proc.,1st Int. Confon Hydroinformatics, Balkema, Rotterdam, The Netherlands,1994.225～231
[29]. Robin Wardlaw, Mohd Sharif. Evaluation of Genetic Algorithms for Optimal Reservoir System Operation. Journal of Water Resources Planning And Management. 1999,125 (1):25-33
[30].Ramesh S. V. Teegavarapu, Slobodan P. Simonovic. Optimal Operation of Reservoir Systems using Simulated Annealing. Water Resources Management.2002,16(5):401-428
[31]. AKTER T,SIMONOVIC S P.Modelling uncertainties in short-term reservoir operation using fuzzy sets and a genetic algorithm. Hydrological Sciences Journal.2004,49(6): 1081～1097
[32]. AHMED J A,SARMA A K.Genetic algorithm for optimal operating policy of a multipurpose reservoir. Water Resources Management.2005,19(2):145～161
[33]. HUANG Wen-cheng, YUAN. Lun-chin. A drought early warning system on real-time multireservoir operations. Water Resources Research.2004,40 (6):10～29
[34]. Yu B,Yang Z,Cheng C,et al.Optimizing Bus Tran-sit Network With Parallel Ant Colony Algorithm. Proceedings of the Eastern Asia Society for Transportation Studies.2005:374～389
[35].Milutin, D. Multiunit water resource system management by decomposition, optimization and emulated evolution-a case study of seven water supply reservoirs in Tunisia, Doctoral dissertation, Wangeningen Agricultural University, The Netherlands,1998
[36]. Zhao Hongwei, Ren Zhen. Hydro-thermal commitment considering pumped storage stations.IEEE Proceedings of International Conference on Power System Technology (POWERCON'98),Vol.1,Beijing,China.1998.576～580.
[37]. Guan Xiaohong, Roang Peter.Optimizition-based scheduling of hydrothermal power systems with pumped storage. IEEE Trans on PS.1994,9(2):1023～1031
[38].谭维炎,刘健民,黄守信,等.应用随机动态规划进行水电站水库的优化调度.水利学报,1982,(7)：1-7
[39].张勇传,熊斯毅,李福生,等.拓溪水电站水库优化调度,见：优化理论在水库调度中的应用.长沙：湖南科学技术出版社,1985,1-4
[40].董子敖,闫建生,尚忠昌,等.改变约束法和国民经济效益最大准则在水电站水库优化调度中的应用.水力发电学报,1983,(2)：1-11
[41].施熙灿,林翔岳,梁青福,等.考虑保证率约束的马氏决策规划在水库优化调度中的应用.水力发电学报,1982,(2)：11～21
[42].张勇传,傅昭阳.水库优化调度中的几个理论问题,见：优化理论在水库调度中的应用.长沙：湖南科学技术出版社,1985,28～40
[43].张勇传,邴凤山,熊斯毅.水库优化调度的模糊数学方法,见：优化理路在水库调度中的应用.长沙：湖南科学技术出版社,1985,130～140
[44].陈守煜.多维多目标决策系统模糊优选理论及其应用.水利学报,1990,(1)：1-10
[45].陈守煜,赵瑛琪.系统层次分析模糊优选模型.水利学报,1988,(10)：1-10
[46].张勇传,李福生,熊斯毅,等.水电站水库群优化调度方法的研究.水力发电,1981,(11)：48～52
[47].熊斯毅,邴凤山.湖南拓、马、双、凤水库群联合优化调度,见：优化理论在水库调度中的应用.长沙：湖南科学技术出版社,1985,130～40
[48].叶秉如,许静仪,潘慧玲,等.水电站库群的年最优调度,见：优化理论在水库调度中的应用.长沙：湖南科学技术出版社,1985,65～73
[49].黄守信,方淑秀,姚念念.两个无水力联系水库的优化调度,见：优化理论在水库调度中的应用.长沙：湖南科学技术出版社,1985,85～89
[50].纪昌明.离散微分动态规划法在混联式水电站群动能指标优化中的应用.1983年全国水电中青年科技干部学术交流会论文选集.北京：水利电力出版社,1985.33～39
[51].鲁子林.水库群调度网络分析法.华东水利学院学报,1983,(11)
[52].吴倍益.模糊数学在水库调度中的应用.水力发电.,1985,(5)
[53].董子敖,阎建生.计入径流时间空间相关关系的梯级水库群优化调度的多层次法.水电能源科学,1987,5(1)：29～40
[54].叶秉如等.红水河梯级优化调度的多次动态规划空间分解算法.见：红河水电最优开发数学模型研究论文集.南京：河海大学,1998
[55].胡振鹏,冯尚友等.大系统多目标递阶分析“分解一聚合”方法.系统工程学报.1988,(1)
[56].陈守煜.多阶段多目标决策系统模糊优选理论及其应用.水利学报,1990,(1)：24-30
[57].吴保生,陈惠源.多库防洪系统优化调度的一种解算方法.水利学报,1991(11)：35～40
[58].刘起方,马光文等.对分插值与混沌嵌套搜索算法在梯级水库联合优化调度中的应用.水力学报,2008,39(2)：146～150
[59].纪昌明,冯尚友.可逆性随机动态规划模型及其在库群优化运行中的应用.武汉水利电力大学学报,1993,26(3)：300～306
[60].都金康,周广安.水库群防洪调度的主次优化方法.水科学进展,1994,5(2)：134～141
[61].金菊良.遗传算法在水资源工程中的应用研究：[博士后学位论文],四川：四川大学,2000
[62].畅建霞,黄强等.基于改进遗传算法的水电站水库优化调度.水力发电学报,2001,(3)：85～90
[63].王大刚,程春田等.遗传算法的水电站优化调度研究.华北水利水电学院学报,2001,(3)：5-10
[64].王小安,李承军.遗传算法在短期发电优化调度中的研究与应用.长江科学院院报,2003,(4)：13～15
[65].杜丹等.基于遗传算法的多目标串联水库系统优化调度方法.内蒙古农业大学学报,2004,25(2)：86～90
[66].胡明是等.基于改进遗传算法的水电站日优化调度方法研究.水力发电学报,2004,23(2)：17～21
[67].罗云霞等.基于改进遗传算法的串联小水电群优化调度.水电自动化与大坝监测,2004,28(3)：66～69
[68].马玉新,解建仓,罗军刚.基于方向自学习遗传算法的水库优化调度,2009,28(4)：43～48
[69].胡铁松,万永华,冯尚友.水库群优化调度函数的人工神经网绍方法研究.水科学进展,1995,(3)：53～60
[70].徐刚,马文广,梁武湖,等.蚁群算法在水库优化调度中的应用.水科学进展,2005,16(3)：397～400
[71].王志良,潘文学.混沌蚁群算法在水库优化调度中的应用.水利与建筑工程学报.2007,5(4)：31～34
[72].胡国强,贺仁睦.基于自适应蚁群算法的水电站水库优化调度.中国电力,2007,40(7)：48～50
[73].林剑艺,程春田,于滨,等.基于改进蚁群算法的梯级水库群优化调度.水电能源科学,2008,26(4)：53～55
[74].杨道辉.基于育种算法的水库优化调度.水电自动化与大坝监测,2009,33(5)：72～74
[75].李崇浩,纪昌明,李文武.改进微粒群算法及其在水库优化调度中的应用.中国农村水利水电,2006,(2)：54～56
[76].李安强, 王丽萍,李崇浩,等.免疫粒子群算法在梯级水电厂间负荷优化分配中的应用.水力发电学报,2007,26(5)：15～20
[77].彭勇,梁国华,周惠成.基于改进微粒群算法的梯级水库群优化调度,2009,28(4)：49～48
[78].徐得潜,韩志刚,翟国寿,等.抽水蓄能电站与火电配合运行优化模型研究.水力发电学报,1996,(4)：11～20.
[79]. AlfredHS, WilsonHTan各ProbabilityConceptsinEngineeringPlan andDesi, Volumell, Deeision,凡skandReliability, John WikSons, NewYork,1984
[80].田峰巍,黄强,解建仓水库实施调度及风险决策.水利学报,1998,(3)：58～62.
[81].黄强,苗隆德,王增发.水库调度中的风险分析及决策方法.西安大学学报,1999,(4)：6-10.
[82].胡铁松.水库调度智能决策支持系统理论与应用研究.武汉：水利电力大学,1993
[83].李继清,张玉山,王丽萍等.基于集对分析理论的水电站中长期风险调度问题研究.水文,2006,(4)：21～26.
[84].纪昌明,梅亚东等.水资源工程多目标风险管理-二十一世纪我国水资源战略雏议,水问题论坛,1994,(1)：56～61
[85].傅湘,王丽萍,纪昌明.防洪减灾中多目标决策优化模型.水电能源科学.2001,19(1)：36～39
[86].朱勇华.防洪风险分析的一个Possion标值点过程及其性质,武汉水利水电大学学报,2000,33(3)：180-183
[87].傅湘,陶涛,王丽萍,等.防洪风险决策模型的应用研究.水电能源科学,2001,19(2)：15-18
[88].傅湘,王丽萍,纪昌明.洪灾风险评价通用模型系统的研究.长江流域资源与环境,2000,9(4)：518～524
[89].陈进.防洪工程系统风险分析方法探讨.长江科学院院报,2001,18(5)：37-40
[90].陈进.水工结构目标安全度确定方法探讨.建筑科学,2002,18(增刊)：108～110
[91].程卫帅,陈进.典型防洪工程水位之间相关性分析.建筑科学,2002,18(增刊)：163～166
[92].程卫帅,陈进.相关性对系统可靠度的影响.长江科学院院报,2003,19(3)：60～64
[93].李继清,王丽萍,纪昌明.基于集对分析理论的洪灾综合风险分析模拟模型.计算机工程与应用(增刊),2004,(40)：43-～45
[94].李继清,张玉山,王丽萍,纪昌明.洪灾系统风险的同异反综合分析模型.中国人工智能学会第10届全国学术年会论文集(下),中国人工智能进展(2003),北京邮电大学出版社,中国人工智能学会,2003,1493～1496
[95].李继清,王丽萍,纪昌明.基于集对分析理论的洪灾综合风险分析模拟模型.计算机工程与应用(增刊),2004,(40)：43～45
[96].李继清,张玉山,王丽萍,纪昌明.洪灾综合风险结构与综合评价方法(Ⅰ)宏观方面.武汉大学学报(工学版),2005,38(5)：19～23
[97].李继清,张玉山,王丽萍,纪昌明.洪灾综合风险的结构特征分析.长江流域资源与环境,2005,14(6)：805～809
[98].李继清,张玉山,王丽萍,纪昌明.基于集对分析理论的洪灾综合风险分析研究(Ⅰ),系统工程,2005,(增刊)：185～187
[99].李继清,张玉山,王丽萍,纪昌明.基于集对分析理论的洪灾综合风险分析研究(Ⅱ),系统工程,2005,(增刊)：187～191
[100]. LI Jiqing, JI Chang-ming, Zhang Yushan, WANG Li-ping. Matter-element Model of Integrated Risk Assessment for Flood Control Systems. International Journal of risk assessment and management.2005.12
[101]. Li Jiqing, Ji Changming, Wang Liping, An application of catastrophe theory to social impact assessment of integrated flood risks in Yangze River, International Conference on Reservoir Operation and River Management.2005,17～23
[102]. Li Jiqing, Ji Changming, Wang Liping.Social impact assessment of integrated risks for flood disaster in Yangtze River based on catastrophe theory, International Symposium on Methodology in Hydrology, Dec.,2005
[103].李继清,张玉山,王丽萍,纪昌明.洪灾综合风险结构与综合评价方法(Ⅱ)———微观结构.武汉大学学报(工学版),2006,39(2)：5-10
[104].李继清,张玉山,王丽萍等,洪灾综合风险分析方法讨论1-基于集对分析理论[J].数学的实践与认识,2007,37(8)：43～49
[105].李继清,张玉山,王丽萍,等.洪灾综合风险分析方法讨论2-基于集对分析理论[J].数学的实践与认识,2007,37(9)：51～57
[106]. Ben-Chie Yen. Risk in hydrologic design of engineering project. Proceeding ASCE.Hy,1970,196
[107]. Ben-Chie Yen-Stochastic methods and reliability analysis in water resources-Water Resources Research,24(9):213～224
[108]. Ribeiro AA-Criteria for the construction diversion floods and cofferdams. ICOLD, 1988, Q63, R 7:69～78
[109]. Karlsson D O, Haimes Y Y-Probability distributions and their partitioning.Water Resources Research,24(1):21～29
[110].邓永录,梁之舜.随机点过程及其应用,北京：科学出版社,1992
[111].邓永录,徐宗学.洪水风险率分析的更新过程模型与应用.水电能源科学,1989,(3)：226～232
[112].徐宗学.洪水风险率CSPPC模型及其应用.水利学报,1988,(9)：1-9
[113].肖焕雄,韩采燕·施工导流系统超标洪水风险率模型研究.水利学报,1993,(11)：76～83
[114].肖焕雄,孙志禹.不漫堰围堰超标洪水风险率计算.水利学报,1996,(2)：37～42
[115].胡志根,刘全等.基于Monte-Carlo方法的土石围堰挡水导流风险分析.水科学进展,2002,(5)：634～639
[116].姜树海.水库调洪演算的随机模拟数学模型.水科学进展,1993,4(4)：294-300
[117].姜树海.防洪设计标准和大坝防洪安全.水利学报,1999,(5)：19～25
[118].石明华,钟登华.施工导流超标洪水风险率估计的水文模拟方法.水利学报,1998,(3)：30～33
[119].长江水利委员会.水利水电工程设计洪水计算手册.北京：水利电力出版社,1995
[120].刘东海,钟登华等.基于日径流模拟的围堰实时挡水风险率估计.水利学报,2001,(3)：27～31
[121]. KirkPartick S, Gelatt C D, Veechi M P. Optimization by simulated annealing. Seienee.1983,220:671～680
[122]. Fogel L J. Evolutionary Programming in perspective:the Top-down View, in Computational Intelligence:Imitating Life. IEEE press, Piscataway, NJ,1994
[123]. Holland J H Adaptation in natural and artificial systems. Boston:MIT Press,1992
[124]. Li TY, James, A. York, Period Three Means Chaos. American Mathematical Monthly,1975,82:985～992
[125]. May RM, Simple Mathematical Models with Very Complicated Dynamics. Nature,1976,261:959～967
[126]. Warfield J N. Social Systems:Planning, Policy, and Complexity [J]. New York: Wiley Inter-science,1976
[127]. Flood C. Dealing with Complexity,2nd [M]. New York:Plenum Press,1993
[128].李晓磊,邵之江,钱积新.一种基于动物自治体的寻优模式：鱼群算法.系统工程理论与实践,2002,22(11)：32～38.
[129]. Shi Y, Eberhart R C.A Modified Particle Swarm Optimizer [A]. IEEE World Congress on Computational Intelligence [C]:IEEE,1998,1951～1957
[130]. Shi Y, Eberhart R C. Empirical Study of Particle Swarm Optimization. In: Proceedings of the 1999 Congress on Evolutionary Computation. Piscataway, NJ, IEEE Service Center,1999,1945～1950
[131].曾建潮,介婧,崔志华.微粒群算法.北京：科学出版社.2004.257～268
[132].谢晓锋,张文俊,杨之廉.微粒群算法综述.控制与决策,2003, 18(2)：129～134
[133].李宁,付国江,库少平等.粒子群优化算法的发展与展望.武汉理工大学学报,2005,27(2)：26～29
[134]. Kennedy J, Eberhart R C. Particle Swarm Optimization. IEEE International Conf. on Neural Networks. Perth, Australia IEEE,1995,1942～1948
[135]. Kennedy J, Eberhart R C. A new optimizer using particle swarm theory. Proc. of the Sixth International Symposium on Micro Machine and Human Science, Nagoya, Japan,1995:39～43
[136]. shiEberhart RC and Shi Y, Comparing inertia weights and constriction factors in Particle Swarm Optimization. Proceedings of the Congress on Evolutionary Computating 2000:84～88
[137]. Asanga Ratnaweera, Saman K. Halgamuge, Member, IEEE, and Harry C. Watson. Self-Organizing H-ierarchical Particle Swarm Optimizer With Time-VaryingAcceleration Coefficients. IEEE TRANSACTIONS ON EVOLUTIONARY COMPUTATION, VOL.8, NO.3, JUNE 2004,240～255
[138]. M.Clerc, The Swarm and the Queen:Toward a Dete rministic and Adaptive Particle Swarm Optimizatio n, Proc. of the Congress on Evolutionary Computation, 1951-1957, Washington, DC,1999
[139].李安强,王丽萍等.基于免疫粒子群优化算法的梯级水电厂间符合优化分配.水力发电学报,2007,26(5)：15-20
[140].胡国强,梯级水电站优化调度模型与算法研究：[博士学位论文],北京：华北电力大学,2007
[141].郝柏林.从抛物线谈起——空气动力学引论.上海：上海科技教育出版社,1997.25～39
[142].李兵,蒋慰孙.混沌优化方法及其应用.控制理论与应用.1997,14,(4)：613-615
[143].单梁,强浩,李军,等.基于Tent映射的混沌优化算法.控制与决策,2005,(2)：179～182.
[144].白小勇,王晨华,李充军,等.人工鱼群算法与离散微分动态规划结合在水库优化调度中的应用.水电自动化与大坝检测,2008,29(3)：135～138
[145].张验科.防洪工程洪水调度风险分析及计算方法研究：[硕士学位论文].北京：华北电力大学.2006
[146].吕满英.考虑洪水过程不确定性的泄洪风险分析：[硕士学位论文].新疆：新疆农业大学.2002
[147].管新建,张文鸽.水库防洪调度风险分析研究进展与发展趋势.防汛抗旱,2004：44～45
[148].贺志岗.随机模拟法在汉江中游设计洪水计算中的应用研究：[硕士学位论文].南京：河海大学,2005
[149].李继清,张玉山,王丽萍,纪昌明.洪水资源化及其风险管理浅析.人民长 江,2005,36(1)：36～37.
[150].纪昌明,李继清,张玉山.防洪工程体系综合风险评价的物元模型.华北电力大学学报,2005,32(1)：86～90
[151].张验科,王丽萍,等.水电厂竞价电量的风险分析模型及应用.水电自动化与大坝检测,2006,30(6)：27～30
[152].姜生斌.基于免疫微粒群算法的梯级水电站水库优化调度研究：[硕士学位论文].北京：华北电力大学,2007
[153].王岩,隋思涟,王爱青.数理统计与matlab工程数据分析.北京：清华大学出版社,2006.89～101
[154].熊福生.风险理论.武汉：武汉大学出版社,2005
[155].陈守煌.堤防设计洪水风险分析.黑龙江水专学报,2001,28(4)：1-3
[156].朱勇华,郭海晋,等.防洪堤防防洪综合风险研究.中国农村水利水电,2003(7)：11～14
[157].吴兴征,赵进勇.堤防风险分析理论及其应用.水利学报,2003,8(8)：79～85
[158].王蕊.水电市场化运营的电量配置问题研究：[硕士论文].北京：华北电力大学,2007
[159].苏学灵,纪昌明,黄小锋等.混合式抽水蓄能电站在梯级水电站群中的优化调度及效益研究.电力系统自动化,2010,34(4)：29～33
[160].王少波,解建仓,孔珂.自适应遗传算法在水库优化调度中的应用.水力学报,2006,37(4)：480～485
[161].张勇传.优化理论在水库调度中的应用.长沙：湖南科技出版社,1985.
[162].涂启玉,梅亚东.遗传模拟退火和小生境遗传算法在水库优化调度中的比较.水电自动化与大坝监测,2008,32(4)：1-4
[163].卢华友,郭元裕.利用多层递阶回归分析制定水库优化调度函数的研究.水利学报,1998,12(13)：71～76
[164].缪益平,纪昌明.运用改进神经网络算法建立水库调度函数.武汉大学学报(工学版),2003,36(1)：83～89
[165].韩志刚.时间序列的多层分析方法初步及应用.黑龙江大学自然科学学报,1985,(1)
[166].刘攀,郭生练,庞博等.三峡水库运行初期蓄水调度函数的神经网络模型研究及改进[J].水力发电学报,2006,25(2)：11～15,46
[167].李承军,陈毕胜,张高峰.水电站双线性调度规则研究.水力发电学报,2005,24(1)：11～15,46
[168].丁杰华.水库水电站群长期运行规律研究：[博士学位论文].武汉：武汉大学,2005
[169].黄胜.灰色系统与多元逐步回归耦合模型在年用水量预测中的应用.节水灌溉,2007,5：38～40
[170].康重庆,夏清,刘梅,等.应用于负荷预测中的回归分析的特殊问题.电力系统自 动化,1998,22(10)：38～41,49
[171].周晓阳,马寅午,张勇传.梯级水库的参数辨识型优化调度方法(Ⅱ)——最优调度函数的确定.水力发电学报,1999,9(9)：10～19
[172].冯文琪.混合式抽水蓄能电站优化调度及效益评估研究：[博士学位论文].武汉：武汉大学,2006
[173].朱勇华,郭海晋,等.防洪堤防防洪综合风险研究.中国农村水利水电,2003,(7)：11-14
[174].吴兴征,赵进勇.堤防风险分析理论及其应用.水利学报,3003,8(8)：79～85
[175]].席秋义.水库(群)防洪安全风险率模型和防洪标准研究：[博士学位论文].西安：西安理工大学,2006
[176].纪昌明,梅亚东.防洪风险分析.武汉：湖北科学技术出版社,2002.18～66
[177].姜树海.洪灾风险评估和防洪安全决策.北京：中国水利水电出版社,2005,128～156
[178].姜树海.水库调洪演算的随机数学模型.水科学进展,1993,4(4)：294～300
[179].肖焕雄.施工水力学.北京：水利电力出版社,1992.46～67
[180].盛乐民.向家坝水电站施工组织设计简介.水力发电,1998,(2)：16～19
[181].王文圣,丁晶,等.随机水文学.北京：水利电力出版社,2008
[182].胡铁松.神经网络预测与优化.大连：大连海事大学出版社,1997
[183].焦李成.神经网络计算.西安：西安电子科技大学出版社,1993
[184].纪昌明,苏学灵,彭杨.汛期横江入流对向家坝一期围堰河段水位的顶托影响.节水灌溉,2009,(4)：65～68
[185].张虎成,魏浪,张习传.水利水电建设项目后评价研究现状与发展趋势.贵州水力发电,2007,21(5)：12～15
[186].王连芬,许树柏.层次分析法引论,北京：中国人民大学出版社,1990
[187].冯尚友.多目标决策理论方法与应用.武汉：华中理工大学出版社,1990
[188].王兴菊,赵然杭.水库多目标优化调度理论及其应用研究.水利学报,2003,(3)：104～109
[189].倪建军,徐立中,李臣明.水库调度决策研究综述.水利水电科技进展,2004,24(6)：63～66
[190].朱旭萍,廖昕宇,唐德善.辽河流域防洪体系治涝效益分析与评价.水力发电,2007,33(3)：23～25
[191].陈守煜,李庆国.多指标半结构性模糊评价法在水利工程后评价中的应用.水利学报,2004,(4)：27～32
[192].Ferko Bodnar, Wim Spaan, Jasper Hulshof. Ex-post evaluation of erosion control measures in southern Mali.Soil and Tillage,2007,95 (1-2):27～37
[193]. Andrea Castelletti, Rodolfo Soncini Sessa.Topics on System Analysis and Integrated Water Resources Management.Amsterdam:Elsevier,2007
[194].肖宜.不完全信息下水利工程后评价方法及应用研究：[学位论文].武汉：武汉大学,2007
[195].徐泽水.不确定多属性决策方法及应用.北京：清华大学出版社,2004
[196].徐玖平,吴巍.多属性决策的理论与方法.北京：清华大学出版社,2006
[197].李祚泳,汪嘉杨,熊建秋,等.可持续发展评价模型与应用.北京：科学出版社,2007
[198].陈忠琏.多元数据分析的PP方法.数理统计与应用概率,1986,1(2)：103～124
[199].刘宝啶,赵瑞清,王纲.不确定性规划及应用.北京：清华大学出版社,2005
[200].乔云峰,夏军,纪昌明,等.投影寻踪法在径流还原计算中的应用研究.水力发电学报,2007,26(1)：6-10
[201].吴运卿,邵东国,肖宜.湖南四水治理项目对流域经济发展影响的定量分析.武汉大学学报(工学版),2006,39(2)：32～35
[202].曾启明,邵东国,刘丙军,等.湖南省四水治理项目效益分析.中国农村水利水电,2005,(7)：94～97
[2].果瑞金.混合式抽水蓄能电站优化调度刍议.水利水电技术,1997,28(3)：44～46
[3].陆佑楣,潘家净.抽水蓄能电站.北京：水利电力出版社,1992.24-38
[4].周之豪,陈崇仁,王海曙.抽水蓄能电站建设的新发展.河海大学科技情报,1989,9(3)：1-8
[5]. International water power and dam construction 1997 year book. Wilmington Business Publshing,1997
[6].Cgeol MSc Dic FGS. Pumped storage part II:North Amarica Africa and Asia.International Wa-ter Power and Dam Construction.1995,47(7):34～36
[7]. Cheng Xuemin. Recent progress in pumped strage schemes in China.International Water Power and Dam Construction,1993,45(2):16～19
[8].唐文化,李小燕,李友起.潘家口抽水蓄能电站水能参数的设计.水力发电,1995,(8)：40～61
[9].陈文.响洪甸混合式抽水蓄能电站工程特点.水利水电技术,1996,(10)：14～53
[10].王平,冯庆华,邱玉怀.响洪甸混合式抽水蓄能工程的运行方式和综合效益.水利水电技术,2000,31(2)：11～13
[11]. J. D. C.Little. The use of storage water in a hydroelectric system, oper. Res,3,1995
[12]. Gagnon, C. R., R. H, Hicks, S. L. S. Jacoby, et al. A Nonlinear Programming Approach to a Very Large Hydroelectric System Optimization. Math. Program.1974.6:28～41,
[13]. Larson, R.E., State Incremental Dynamic Programming, Elsevier, New York,1968
[14].Trott, W.J, and W.W G..Yeh, Optimization of Multiple reservoir systems, J.Hhdraul. Div. Am. Soe. Civ. Eng.1983,99(Hy10):1865～1844
[15]. Giles. J. E, and W.O., Wunderlick, Weekly multipurpose planning model for TVA reservoir system, J. of the Water Resour, Plann. Manage.Div. Am. Soe. Civ. Eng.1981,107(WR2):495～511,
[16]. Murray, D. M. and S.J. Yakowitz, Constrained differential dynamic Progrmaming and its application to multireservoir control, Water Resour. Res.1979,15(5):1017-1027,
[17].TurgeonA., optimal short-term hydro scheduling from the principle of progressive optimality, Water Resour. Res.1981,17(3):481～486,
[18].Howson, H.R., and N.C.F. Saneho, A new algorithm for the solution of multistate dynamic programming problems, Math. Programm.1975,8(1):35～41
[19]. Arvanitidis, N.V, and J. Rosing, optimal Operation of multireservoir systems using a composite representation, IEEE Transactions on Power apparatus and systems,1970, 89(2)
[20].Heidari M, Chow V T, Kokotovie P V, et al.Diserete Differential Dynamic Programming Approach to Water Resources Systems Optimization.Water Resour. Res.,1971,7(2):155～164
[21]. Larson, R.E., State Incremental Dynamic Programming, Elsevier, New York,1968
[22].Trott, W.J, and W.W G.Yeh, Optimization of Multiple reservoir systems, J.Hhdraul. Div. Am. Soe. Civ. Eng.,1983,99(10):1865～1844,
[23]. Giles. J. E, and W.O., Wunderlick, Weekly multipurpose planning model for TVA reservoir system, J. of the Water Resour, Plann. Manage.Div. Am. Soe. Civ. Eng.1981,107(2):495～511,
[24]. Murray, D. M. and S.J. Yakowitz, Constrained differential dynamic Progrmaming and its application to multireservoir control, Water Resour. Res.1979,15(5):1017～1027,
[25].TurgeonA., optimal short-term hydro scheduling from the principle of progressive optimality, Water Resour. Res.1981,17(3):481～486,
[26].Howson, H.R., and N.C.F. Saneho, A new algorithm for the solution of multistate dynamic programming problems, Math. Programm.1975,8(1)
[27]. Marino, M.A., and B. Mohammadi, Reservoir operation by linear and dynamic programming, J. Water Resour. Plann. Manage.,1983,104(4):25～32
[28].Esat, V., and Hall, M. J.. Water Resources System Optimization Using Genetic Algorithms. Hydroinformatics'94, Proc.,1st Int. Confon Hydroinformatics, Balkema, Rotterdam, The Netherlands,1994.225～231
[29]. Robin Wardlaw, Mohd Sharif. Evaluation of Genetic Algorithms for Optimal Reservoir System Operation. Journal of Water Resources Planning And Management. 1999,125 (1):25-33
[30].Ramesh S. V. Teegavarapu, Slobodan P. Simonovic. Optimal Operation of Reservoir Systems using Simulated Annealing. Water Resources Management.2002,16(5):401-428
[31]. AKTER T,SIMONOVIC S P.Modelling uncertainties in short-term reservoir operation using fuzzy sets and a genetic algorithm. Hydrological Sciences Journal.2004,49(6): 1081～1097
[32]. AHMED J A,SARMA A K.Genetic algorithm for optimal operating policy of a multipurpose reservoir. Water Resources Management.2005,19(2):145～161
[33]. HUANG Wen-cheng, YUAN. Lun-chin. A drought early warning system on real-time multireservoir operations. Water Resources Research.2004,40 (6):10～29
[34]. Yu B,Yang Z,Cheng C,et al.Optimizing Bus Tran-sit Network With Parallel Ant Colony Algorithm. Proceedings of the Eastern Asia Society for Transportation Studies.2005:374～389
[35].Milutin, D. Multiunit water resource system management by decomposition, optimization and emulated evolution-a case study of seven water supply reservoirs in Tunisia, Doctoral dissertation, Wangeningen Agricultural University, The Netherlands,1998
[36]. Zhao Hongwei, Ren Zhen. Hydro-thermal commitment considering pumped storage stations.IEEE Proceedings of International Conference on Power System Technology (POWERCON'98),Vol.1,Beijing,China.1998.576～580.
[37]. Guan Xiaohong, Roang Peter.Optimizition-based scheduling of hydrothermal power systems with pumped storage. IEEE Trans on PS.1994,9(2):1023～1031
[38].谭维炎,刘健民,黄守信,等.应用随机动态规划进行水电站水库的优化调度.水利学报,1982,(7)：1-7
[39].张勇传,熊斯毅,李福生,等.拓溪水电站水库优化调度,见：优化理论在水库调度中的应用.长沙：湖南科学技术出版社,1985,1-4
[40].董子敖,闫建生,尚忠昌,等.改变约束法和国民经济效益最大准则在水电站水库优化调度中的应用.水力发电学报,1983,(2)：1-11
[41].施熙灿,林翔岳,梁青福,等.考虑保证率约束的马氏决策规划在水库优化调度中的应用.水力发电学报,1982,(2)：11～21
[42].张勇传,傅昭阳.水库优化调度中的几个理论问题,见：优化理论在水库调度中的应用.长沙：湖南科学技术出版社,1985,28～40
[43].张勇传,邴凤山,熊斯毅.水库优化调度的模糊数学方法,见：优化理路在水库调度中的应用.长沙：湖南科学技术出版社,1985,130～140
[44].陈守煜.多维多目标决策系统模糊优选理论及其应用.水利学报,1990,(1)：1-10
[45].陈守煜,赵瑛琪.系统层次分析模糊优选模型.水利学报,1988,(10)：1-10
[46].张勇传,李福生,熊斯毅,等.水电站水库群优化调度方法的研究.水力发电,1981,(11)：48～52
[47].熊斯毅,邴凤山.湖南拓、马、双、凤水库群联合优化调度,见：优化理论在水库调度中的应用.长沙：湖南科学技术出版社,1985,130～40
[48].叶秉如,许静仪,潘慧玲,等.水电站库群的年最优调度,见：优化理论在水库调度中的应用.长沙：湖南科学技术出版社,1985,65～73
[49].黄守信,方淑秀,姚念念.两个无水力联系水库的优化调度,见：优化理论在水库调度中的应用.长沙：湖南科学技术出版社,1985,85～89
[50].纪昌明.离散微分动态规划法在混联式水电站群动能指标优化中的应用.1983年全国水电中青年科技干部学术交流会论文选集.北京：水利电力出版社,1985.33～39
[51].鲁子林.水库群调度网络分析法.华东水利学院学报,1983,(11)
[52].吴倍益.模糊数学在水库调度中的应用.水力发电.,1985,(5)
[53].董子敖,阎建生.计入径流时间空间相关关系的梯级水库群优化调度的多层次法.水电能源科学,1987,5(1)：29～40
[54].叶秉如等.红水河梯级优化调度的多次动态规划空间分解算法.见：红河水电最优开发数学模型研究论文集.南京：河海大学,1998
[55].胡振鹏,冯尚友等.大系统多目标递阶分析“分解一聚合”方法.系统工程学报.1988,(1)
[56].陈守煜.多阶段多目标决策系统模糊优选理论及其应用.水利学报,1990,(1)：24-30
[57].吴保生,陈惠源.多库防洪系统优化调度的一种解算方法.水利学报,1991(11)：35～40
[58].刘起方,马光文等.对分插值与混沌嵌套搜索算法在梯级水库联合优化调度中的应用.水力学报,2008,39(2)：146～150
[59].纪昌明,冯尚友.可逆性随机动态规划模型及其在库群优化运行中的应用.武汉水利电力大学学报,1993,26(3)：300～306
[60].都金康,周广安.水库群防洪调度的主次优化方法.水科学进展,1994,5(2)：134～141
[61].金菊良.遗传算法在水资源工程中的应用研究：[博士后学位论文],四川：四川大学,2000
[62].畅建霞,黄强等.基于改进遗传算法的水电站水库优化调度.水力发电学报,2001,(3)：85～90
[63].王大刚,程春田等.遗传算法的水电站优化调度研究.华北水利水电学院学报,2001,(3)：5-10
[64].王小安,李承军.遗传算法在短期发电优化调度中的研究与应用.长江科学院院报,2003,(4)：13～15
[65].杜丹等.基于遗传算法的多目标串联水库系统优化调度方法.内蒙古农业大学学报,2004,25(2)：86～90
[66].胡明是等.基于改进遗传算法的水电站日优化调度方法研究.水力发电学报,2004,23(2)：17～21
[67].罗云霞等.基于改进遗传算法的串联小水电群优化调度.水电自动化与大坝监测,2004,28(3)：66～69
[68].马玉新,解建仓,罗军刚.基于方向自学习遗传算法的水库优化调度,2009,28(4)：43～48
[69].胡铁松,万永华,冯尚友.水库群优化调度函数的人工神经网绍方法研究.水科学进展,1995,(3)：53～60
[70].徐刚,马文广,梁武湖,等.蚁群算法在水库优化调度中的应用.水科学进展,2005,16(3)：397～400
[71].王志良,潘文学.混沌蚁群算法在水库优化调度中的应用.水利与建筑工程学报.2007,5(4)：31～34
[72].胡国强,贺仁睦.基于自适应蚁群算法的水电站水库优化调度.中国电力,2007,40(7)：48～50
[73].林剑艺,程春田,于滨,等.基于改进蚁群算法的梯级水库群优化调度.水电能源科学,2008,26(4)：53～55
[74].杨道辉.基于育种算法的水库优化调度.水电自动化与大坝监测,2009,33(5)：72～74
[75].李崇浩,纪昌明,李文武.改进微粒群算法及其在水库优化调度中的应用.中国农村水利水电,2006,(2)：54～56
[76].李安强, 王丽萍,李崇浩,等.免疫粒子群算法在梯级水电厂间负荷优化分配中的应用.水力发电学报,2007,26(5)：15～20
[77].彭勇,梁国华,周惠成.基于改进微粒群算法的梯级水库群优化调度,2009,28(4)：49～48
[78].徐得潜,韩志刚,翟国寿,等.抽水蓄能电站与火电配合运行优化模型研究.水力发电学报,1996,(4)：11～20.
[79]. AlfredHS, WilsonHTan各ProbabilityConceptsinEngineeringPlan andDesi, Volumell, Deeision,凡skandReliability, John WikSons, NewYork,1984
[80].田峰巍,黄强,解建仓水库实施调度及风险决策.水利学报,1998,(3)：58～62.
[81].黄强,苗隆德,王增发.水库调度中的风险分析及决策方法.西安大学学报,1999,(4)：6-10.
[82].胡铁松.水库调度智能决策支持系统理论与应用研究.武汉：水利电力大学,1993
[83].李继清,张玉山,王丽萍等.基于集对分析理论的水电站中长期风险调度问题研究.水文,2006,(4)：21～26.
[84].纪昌明,梅亚东等.水资源工程多目标风险管理-二十一世纪我国水资源战略雏议,水问题论坛,1994,(1)：56～61
[85].傅湘,王丽萍,纪昌明.防洪减灾中多目标决策优化模型.水电能源科学.2001,19(1)：36～39
[86].朱勇华.防洪风险分析的一个Possion标值点过程及其性质,武汉水利水电大学学报,2000,33(3)：180-183
[87].傅湘,陶涛,王丽萍,等.防洪风险决策模型的应用研究.水电能源科学,2001,19(2)：15-18
[88].傅湘,王丽萍,纪昌明.洪灾风险评价通用模型系统的研究.长江流域资源与环境,2000,9(4)：518～524
[89].陈进.防洪工程系统风险分析方法探讨.长江科学院院报,2001,18(5)：37-40
[90].陈进.水工结构目标安全度确定方法探讨.建筑科学,2002,18(增刊)：108～110
[91].程卫帅,陈进.典型防洪工程水位之间相关性分析.建筑科学,2002,18(增刊)：163～166
[92].程卫帅,陈进.相关性对系统可靠度的影响.长江科学院院报,2003,19(3)：60～64
[93].李继清,王丽萍,纪昌明.基于集对分析理论的洪灾综合风险分析模拟模型.计算机工程与应用(增刊),2004,(40)：43-～45
[94].李继清,张玉山,王丽萍,纪昌明.洪灾系统风险的同异反综合分析模型.中国人工智能学会第10届全国学术年会论文集(下),中国人工智能进展(2003),北京邮电大学出版社,中国人工智能学会,2003,1493～1496
[95].李继清,王丽萍,纪昌明.基于集对分析理论的洪灾综合风险分析模拟模型.计算机工程与应用(增刊),2004,(40)：43～45
[96].李继清,张玉山,王丽萍,纪昌明.洪灾综合风险结构与综合评价方法(Ⅰ)宏观方面.武汉大学学报(工学版),2005,38(5)：19～23
[97].李继清,张玉山,王丽萍,纪昌明.洪灾综合风险的结构特征分析.长江流域资源与环境,2005,14(6)：805～809
[98].李继清,张玉山,王丽萍,纪昌明.基于集对分析理论的洪灾综合风险分析研究(Ⅰ),系统工程,2005,(增刊)：185～187
[99].李继清,张玉山,王丽萍,纪昌明.基于集对分析理论的洪灾综合风险分析研究(Ⅱ),系统工程,2005,(增刊)：187～191
[100]. LI Jiqing, JI Chang-ming, Zhang Yushan, WANG Li-ping. Matter-element Model of Integrated Risk Assessment for Flood Control Systems. International Journal of risk assessment and management.2005.12
[101]. Li Jiqing, Ji Changming, Wang Liping, An application of catastrophe theory to social impact assessment of integrated flood risks in Yangze River, International Conference on Reservoir Operation and River Management.2005,17～23
[102]. Li Jiqing, Ji Changming, Wang Liping.Social impact assessment of integrated risks for flood disaster in Yangtze River based on catastrophe theory, International Symposium on Methodology in Hydrology, Dec.,2005
[103].李继清,张玉山,王丽萍,纪昌明.洪灾综合风险结构与综合评价方法(Ⅱ)———微观结构.武汉大学学报(工学版),2006,39(2)：5-10
[104].李继清,张玉山,王丽萍等,洪灾综合风险分析方法讨论1-基于集对分析理论[J].数学的实践与认识,2007,37(8)：43～49
[105].李继清,张玉山,王丽萍,等.洪灾综合风险分析方法讨论2-基于集对分析理论[J].数学的实践与认识,2007,37(9)：51～57
[106]. Ben-Chie Yen. Risk in hydrologic design of engineering project. Proceeding ASCE.Hy,1970,196
[107]. Ben-Chie Yen-Stochastic methods and reliability analysis in water resources-Water Resources Research,24(9):213～224
[108]. Ribeiro AA-Criteria for the construction diversion floods and cofferdams. ICOLD, 1988, Q63, R 7:69～78
[109]. Karlsson D O, Haimes Y Y-Probability distributions and their partitioning.Water Resources Research,24(1):21～29
[110].邓永录,梁之舜.随机点过程及其应用,北京：科学出版社,1992
[111].邓永录,徐宗学.洪水风险率分析的更新过程模型与应用.水电能源科学,1989,(3)：226～232
[112].徐宗学.洪水风险率CSPPC模型及其应用.水利学报,1988,(9)：1-9
[113].肖焕雄,韩采燕·施工导流系统超标洪水风险率模型研究.水利学报,1993,(11)：76～83
[114].肖焕雄,孙志禹.不漫堰围堰超标洪水风险率计算.水利学报,1996,(2)：37～42
[115].胡志根,刘全等.基于Monte-Carlo方法的土石围堰挡水导流风险分析.水科学进展,2002,(5)：634～639
[116].姜树海.水库调洪演算的随机模拟数学模型.水科学进展,1993,4(4)：294-300
[117].姜树海.防洪设计标准和大坝防洪安全.水利学报,1999,(5)：19～25
[118].石明华,钟登华.施工导流超标洪水风险率估计的水文模拟方法.水利学报,1998,(3)：30～33
[119].长江水利委员会.水利水电工程设计洪水计算手册.北京：水利电力出版社,1995
[120].刘东海,钟登华等.基于日径流模拟的围堰实时挡水风险率估计.水利学报,2001,(3)：27～31
[121]. KirkPartick S, Gelatt C D, Veechi M P. Optimization by simulated annealing. Seienee.1983,220:671～680
[122]. Fogel L J. Evolutionary Programming in perspective:the Top-down View, in Computational Intelligence:Imitating Life. IEEE press, Piscataway, NJ,1994
[123]. Holland J H Adaptation in natural and artificial systems. Boston:MIT Press,1992
[124]. Li TY, James, A. York, Period Three Means Chaos. American Mathematical Monthly,1975,82:985～992
[125]. May RM, Simple Mathematical Models with Very Complicated Dynamics. Nature,1976,261:959～967
[126]. Warfield J N. Social Systems:Planning, Policy, and Complexity [J]. New York: Wiley Inter-science,1976
[127]. Flood C. Dealing with Complexity,2nd [M]. New York:Plenum Press,1993
[128].李晓磊,邵之江,钱积新.一种基于动物自治体的寻优模式：鱼群算法.系统工程理论与实践,2002,22(11)：32～38.
[129]. Shi Y, Eberhart R C.A Modified Particle Swarm Optimizer [A]. IEEE World Congress on Computational Intelligence [C]:IEEE,1998,1951～1957
[130]. Shi Y, Eberhart R C. Empirical Study of Particle Swarm Optimization. In: Proceedings of the 1999 Congress on Evolutionary Computation. Piscataway, NJ, IEEE Service Center,1999,1945～1950
[131].曾建潮,介婧,崔志华.微粒群算法.北京：科学出版社.2004.257～268
[132].谢晓锋,张文俊,杨之廉.微粒群算法综述.控制与决策,2003, 18(2)：129～134
[133].李宁,付国江,库少平等.粒子群优化算法的发展与展望.武汉理工大学学报,2005,27(2)：26～29
[134]. Kennedy J, Eberhart R C. Particle Swarm Optimization. IEEE International Conf. on Neural Networks. Perth, Australia IEEE,1995,1942～1948
[135]. Kennedy J, Eberhart R C. A new optimizer using particle swarm theory. Proc. of the Sixth International Symposium on Micro Machine and Human Science, Nagoya, Japan,1995:39～43
[136]. shiEberhart RC and Shi Y, Comparing inertia weights and constriction factors in Particle Swarm Optimization. Proceedings of the Congress on Evolutionary Computating 2000:84～88
[137]. Asanga Ratnaweera, Saman K. Halgamuge, Member, IEEE, and Harry C. Watson. Self-Organizing H-ierarchical Particle Swarm Optimizer With Time-VaryingAcceleration Coefficients. IEEE TRANSACTIONS ON EVOLUTIONARY COMPUTATION, VOL.8, NO.3, JUNE 2004,240～255
[138]. M.Clerc, The Swarm and the Queen:Toward a Dete rministic and Adaptive Particle Swarm Optimizatio n, Proc. of the Congress on Evolutionary Computation, 1951-1957, Washington, DC,1999
[139].李安强,王丽萍等.基于免疫粒子群优化算法的梯级水电厂间符合优化分配.水力发电学报,2007,26(5)：15-20
[140].胡国强,梯级水电站优化调度模型与算法研究：[博士学位论文],北京：华北电力大学,2007
[141].郝柏林.从抛物线谈起——空气动力学引论.上海：上海科技教育出版社,1997.25～39
[142].李兵,蒋慰孙.混沌优化方法及其应用.控制理论与应用.1997,14,(4)：613-615
[143].单梁,强浩,李军,等.基于Tent映射的混沌优化算法.控制与决策,2005,(2)：179～182.
[144].白小勇,王晨华,李充军,等.人工鱼群算法与离散微分动态规划结合在水库优化调度中的应用.水电自动化与大坝检测,2008,29(3)：135～138
[145].张验科.防洪工程洪水调度风险分析及计算方法研究：[硕士学位论文].北京：华北电力大学.2006
[146].吕满英.考虑洪水过程不确定性的泄洪风险分析：[硕士学位论文].新疆：新疆农业大学.2002
[147].管新建,张文鸽.水库防洪调度风险分析研究进展与发展趋势.防汛抗旱,2004：44～45
[148].贺志岗.随机模拟法在汉江中游设计洪水计算中的应用研究：[硕士学位论文].南京：河海大学,2005
[149].李继清,张玉山,王丽萍,纪昌明.洪水资源化及其风险管理浅析.人民长 江,2005,36(1)：36～37.
[150].纪昌明,李继清,张玉山.防洪工程体系综合风险评价的物元模型.华北电力大学学报,2005,32(1)：86～90
[151].张验科,王丽萍,等.水电厂竞价电量的风险分析模型及应用.水电自动化与大坝检测,2006,30(6)：27～30
[152].姜生斌.基于免疫微粒群算法的梯级水电站水库优化调度研究：[硕士学位论文].北京：华北电力大学,2007
[153].王岩,隋思涟,王爱青.数理统计与matlab工程数据分析.北京：清华大学出版社,2006.89～101
[154].熊福生.风险理论.武汉：武汉大学出版社,2005
[155].陈守煌.堤防设计洪水风险分析.黑龙江水专学报,2001,28(4)：1-3
[156].朱勇华,郭海晋,等.防洪堤防防洪综合风险研究.中国农村水利水电,2003(7)：11～14
[157].吴兴征,赵进勇.堤防风险分析理论及其应用.水利学报,2003,8(8)：79～85
[158].王蕊.水电市场化运营的电量配置问题研究：[硕士论文].北京：华北电力大学,2007
[159].苏学灵,纪昌明,黄小锋等.混合式抽水蓄能电站在梯级水电站群中的优化调度及效益研究.电力系统自动化,2010,34(4)：29～33
[160].王少波,解建仓,孔珂.自适应遗传算法在水库优化调度中的应用.水力学报,2006,37(4)：480～485
[161].张勇传.优化理论在水库调度中的应用.长沙：湖南科技出版社,1985.
[162].涂启玉,梅亚东.遗传模拟退火和小生境遗传算法在水库优化调度中的比较.水电自动化与大坝监测,2008,32(4)：1-4
[163].卢华友,郭元裕.利用多层递阶回归分析制定水库优化调度函数的研究.水利学报,1998,12(13)：71～76
[164].缪益平,纪昌明.运用改进神经网络算法建立水库调度函数.武汉大学学报(工学版),2003,36(1)：83～89
[165].韩志刚.时间序列的多层分析方法初步及应用.黑龙江大学自然科学学报,1985,(1)
[166].刘攀,郭生练,庞博等.三峡水库运行初期蓄水调度函数的神经网络模型研究及改进[J].水力发电学报,2006,25(2)：11～15,46
[167].李承军,陈毕胜,张高峰.水电站双线性调度规则研究.水力发电学报,2005,24(1)：11～15,46
[168].丁杰华.水库水电站群长期运行规律研究：[博士学位论文].武汉：武汉大学,2005
[169].黄胜.灰色系统与多元逐步回归耦合模型在年用水量预测中的应用.节水灌溉,2007,5：38～40
[170].康重庆,夏清,刘梅,等.应用于负荷预测中的回归分析的特殊问题.电力系统自 动化,1998,22(10)：38～41,49
[171].周晓阳,马寅午,张勇传.梯级水库的参数辨识型优化调度方法(Ⅱ)——最优调度函数的确定.水力发电学报,1999,9(9)：10～19
[172].冯文琪.混合式抽水蓄能电站优化调度及效益评估研究：[博士学位论文].武汉：武汉大学,2006
[173].朱勇华,郭海晋,等.防洪堤防防洪综合风险研究.中国农村水利水电,2003,(7)：11-14
[174].吴兴征,赵进勇.堤防风险分析理论及其应用.水利学报,3003,8(8)：79～85
[175]].席秋义.水库(群)防洪安全风险率模型和防洪标准研究：[博士学位论文].西安：西安理工大学,2006
[176].纪昌明,梅亚东.防洪风险分析.武汉：湖北科学技术出版社,2002.18～66
[177].姜树海.洪灾风险评估和防洪安全决策.北京：中国水利水电出版社,2005,128～156
[178].姜树海.水库调洪演算的随机数学模型.水科学进展,1993,4(4)：294～300
[179].肖焕雄.施工水力学.北京：水利电力出版社,1992.46～67
[180].盛乐民.向家坝水电站施工组织设计简介.水力发电,1998,(2)：16～19
[181].王文圣,丁晶,等.随机水文学.北京：水利电力出版社,2008
[182].胡铁松.神经网络预测与优化.大连：大连海事大学出版社,1997
[183].焦李成.神经网络计算.西安：西安电子科技大学出版社,1993
[184].纪昌明,苏学灵,彭杨.汛期横江入流对向家坝一期围堰河段水位的顶托影响.节水灌溉,2009,(4)：65～68
[185].张虎成,魏浪,张习传.水利水电建设项目后评价研究现状与发展趋势.贵州水力发电,2007,21(5)：12～15
[186].王连芬,许树柏.层次分析法引论,北京：中国人民大学出版社,1990
[187].冯尚友.多目标决策理论方法与应用.武汉：华中理工大学出版社,1990
[188].王兴菊,赵然杭.水库多目标优化调度理论及其应用研究.水利学报,2003,(3)：104～109
[189].倪建军,徐立中,李臣明.水库调度决策研究综述.水利水电科技进展,2004,24(6)：63～66
[190].朱旭萍,廖昕宇,唐德善.辽河流域防洪体系治涝效益分析与评价.水力发电,2007,33(3)：23～25
[191].陈守煜,李庆国.多指标半结构性模糊评价法在水利工程后评价中的应用.水利学报,2004,(4)：27～32
[192].Ferko Bodnar, Wim Spaan, Jasper Hulshof. Ex-post evaluation of erosion control measures in southern Mali.Soil and Tillage,2007,95 (1-2):27～37
[193]. Andrea Castelletti, Rodolfo Soncini Sessa.Topics on System Analysis and Integrated Water Resources Management.Amsterdam:Elsevier,2007
[194].肖宜.不完全信息下水利工程后评价方法及应用研究：[学位论文].武汉：武汉大学,2007
[195].徐泽水.不确定多属性决策方法及应用.北京：清华大学出版社,2004
[196].徐玖平,吴巍.多属性决策的理论与方法.北京：清华大学出版社,2006
[197].李祚泳,汪嘉杨,熊建秋,等.可持续发展评价模型与应用.北京：科学出版社,2007
[198].陈忠琏.多元数据分析的PP方法.数理统计与应用概率,1986,1(2)：103～124
[199].刘宝啶,赵瑞清,王纲.不确定性规划及应用.北京：清华大学出版社,2005
[200].乔云峰,夏军,纪昌明,等.投影寻踪法在径流还原计算中的应用研究.水力发电学报,2007,26(1)：6-10
[201].吴运卿,邵东国,肖宜.湖南四水治理项目对流域经济发展影响的定量分析.武汉大学学报(工学版),2006,39(2)：32～35
[202].曾启明,邵东国,刘丙军,等.湖南省四水治理项目效益分析.中国农村水利水电,2005,(7)：94～97