基于电力市场的汉江上游梯级水电站优化调度研究
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摘要
本论文根据汉江上游梯级的实际情况,对汉江上游已建成的石泉、喜河、安康梯级水电站水库群在电力市场环境下的长期发电优化调度问题进行了研究。在分析了汉江上游径流规律以及电力市场相关内容的基础上,根据该梯级水电站水库群的主要任务及梯级水电站之间的水力联系,建立不同的优化模型并选取优化算法进行求解,对计算结果进行了对比分析;以各水电站发电量统计特征为依据,拟定了梯级各水电站的年度期货电量,并将拟定的期货电量进行了年内分解。论文取得的主要研究成果如下:
(1)对汉江上游1954～1998年44年长系列径流资料进行统计,分析了径流的年内分配、年际变化、代际变化、丰枯变化;采用谱分析方法和坎德尔秩次相关检验分别对径流资料的周期性和趋势性进行了分析。结果表明:汉江上游径流年内、年际分配不均,丰枯差别大,各月均有出现小流量的几率,径流总体呈下降趋势。
(2)根据汉江上游梯级水电站水库群的主要任务以及电力市场中电价因素的影响,建立梯级发电量最大模型和梯级发电效益最大模型,采用逐次逼近动态规划法(DPSA)与逐步优化算法(POA)相结合的混合算法分别求解梯级发电量最大模型和梯级发电效益最大模型。
(3)基于汉江上游径流规律分析结果,划分丰水期为7～9月、枯水期为12～3月、其余月份为平水期,分别选取不同的电价水平,根据不同的丰水期电价下调比例方案进行以梯级发电效益最大为目标的长期优化调度计算,统计各方案的丰、枯电量之比,拟定电价水平取0.2元/kW·h,丰水期电价下调30%,枯水期电价上浮90%。
(4)对比梯级发电量最大模型与梯级发电效益最大模型的计算结果,得出结论:通过优化,可以增加梯级及其各级水电站的发电量,减少各水电站的弃水量,提高水资源的利用率;采用丰、枯季节电价的梯级发电效益最大模型计算得到的多年平均发电量虽然少于梯级发电量最大模型的计算结果,但其发电效益大于梯级发电量最大模型的发电效益;由于考虑了丰、枯季节电价的影响,梯级及其各级水电站增发了枯水期电量,减少了丰水期发电量,其多年平均发电收益的组成结构发生了较大变化,枯水期的发电收益占全年发电收益的比例有了明显提高。
(5)在汉江上游梯级水电站水库群长期发电优化调度的基础上,统计梯级各水电站的年、月发电量特征,制定不同的期货电量划分方案,并对各方案期货电量所占不同典型年发电量的比例进行计算;通过对比分析,拟定石泉、喜河、安康水电站的年度期货电量分别取其各自多年平均发电量的45%,该方案完成期货合约的保证率较高。
(6)按照各水电站各月的可靠电量,将拟定各水电站的年度期货合约电量进行年内分解,分解到各月;石泉、喜河、安康的各月分解电量保证率分别为85%、85%、95%,表明绝大部分来水频率的年份能够完成期货合约。
According to the actual situation, the problem of long-term optimized operation in the electricity market is studied by taking the cascade power stations in the higher reaches of the Hanjiang River as researching objects. After analyzing runoff regularity of the upper Hanjiang River and the relevant content of the electricity market, two optimal models are built and solved by optimal algorithms on the basis of the cascade power stations main task and hydraulic interaction among the stations. By comparatively analyzing the results and making statistics on energy output characteristics, annual future contract energy of each station is determined and distributed to each month within a year. The major work of this dissertation is outlined as follows:
(1)After making statistics on the long-term runoff data of the upper Hanjiang River from 1954 to 1998, annual distribution, annual variation, intergenerational variation and high - low water change of runoff are analyzed. Spectral analysis and Kendall rank correlation coefficient test are adopted to analyze the periodicity and tendency of runoff data. The results show that the annual distribution and annual variation of runoff are uneven, and there is much difference between high and low, and small flow may appear in each month within a year, and the tendency of runoff is reduction.
(2)On the foundation of the main task of this cascade power stations and the influence of tariff, two models of maximizing energy output and maximizing energy benefit are respectively established, and DPSA and POA are combined to solve the models.
(3)Based on the analysis on runoff regularity of the upper Hanjiang River, one year is divided into 3 parts: wet season is from July to September, and dry season is December and from January to March, and the rest is normal season. The maximizing energy benefit model is solved based on the plans of different general tariff and different downward scales of wet season tariff. By making statistics on the ratios of energy output in the wet season to energy output in the dry season of calculation results, the plan is established, which general tariff is 0.2 Yuan per kilo-watt-hour, and downward scales of wet season tariff is thirty percent, and upward scales of dry season tariff is ninety percent.
(4)Comparing the calculation results of two models, it shows that energy output increases and abandoned water decreases by optimized operation. The average annual energy output calculated by maximizing energy benefit model is less than that calculated by maximizing energy output model, but the average annual energy benefit calculated by maximizing energy benefit model is more. As the result of the wet-dry seasonal tariff, energy output in dry season increases and that in wet season decreases. The structure of energy output component has pronounced changed and energy benefit in dry season account for an increasing proportion of annual energy benefit.
(5)According to the calculation results of long-term optimized operation and energy output statistics characteristics, plans of future contract energy are made. By comparing the proportion that future contract energy account for of annual energy output in different typical years, the future contract energy of each station account for forty-five percent of average annual energy output of each station. This plan has higher guaranteed efficiency.
(6)Future contract energy is distributed to each month within a year on the basis of reliable energy output in each month. The guaranteed efficiencies of Shiquan, Xihe and Ankang stations are eighty-five percent, eighty-five percent and ninety-five percent, which show that the future contract will be fulfilled in most of years.
(1)对汉江上游1954～1998年44年长系列径流资料进行统计,分析了径流的年内分配、年际变化、代际变化、丰枯变化;采用谱分析方法和坎德尔秩次相关检验分别对径流资料的周期性和趋势性进行了分析。结果表明:汉江上游径流年内、年际分配不均,丰枯差别大,各月均有出现小流量的几率,径流总体呈下降趋势。
(2)根据汉江上游梯级水电站水库群的主要任务以及电力市场中电价因素的影响,建立梯级发电量最大模型和梯级发电效益最大模型,采用逐次逼近动态规划法(DPSA)与逐步优化算法(POA)相结合的混合算法分别求解梯级发电量最大模型和梯级发电效益最大模型。
(3)基于汉江上游径流规律分析结果,划分丰水期为7～9月、枯水期为12～3月、其余月份为平水期,分别选取不同的电价水平,根据不同的丰水期电价下调比例方案进行以梯级发电效益最大为目标的长期优化调度计算,统计各方案的丰、枯电量之比,拟定电价水平取0.2元/kW·h,丰水期电价下调30%,枯水期电价上浮90%。
(4)对比梯级发电量最大模型与梯级发电效益最大模型的计算结果,得出结论:通过优化,可以增加梯级及其各级水电站的发电量,减少各水电站的弃水量,提高水资源的利用率;采用丰、枯季节电价的梯级发电效益最大模型计算得到的多年平均发电量虽然少于梯级发电量最大模型的计算结果,但其发电效益大于梯级发电量最大模型的发电效益;由于考虑了丰、枯季节电价的影响,梯级及其各级水电站增发了枯水期电量,减少了丰水期发电量,其多年平均发电收益的组成结构发生了较大变化,枯水期的发电收益占全年发电收益的比例有了明显提高。
(5)在汉江上游梯级水电站水库群长期发电优化调度的基础上,统计梯级各水电站的年、月发电量特征,制定不同的期货电量划分方案,并对各方案期货电量所占不同典型年发电量的比例进行计算;通过对比分析,拟定石泉、喜河、安康水电站的年度期货电量分别取其各自多年平均发电量的45%,该方案完成期货合约的保证率较高。
(6)按照各水电站各月的可靠电量,将拟定各水电站的年度期货合约电量进行年内分解,分解到各月;石泉、喜河、安康的各月分解电量保证率分别为85%、85%、95%,表明绝大部分来水频率的年份能够完成期货合约。
According to the actual situation, the problem of long-term optimized operation in the electricity market is studied by taking the cascade power stations in the higher reaches of the Hanjiang River as researching objects. After analyzing runoff regularity of the upper Hanjiang River and the relevant content of the electricity market, two optimal models are built and solved by optimal algorithms on the basis of the cascade power stations main task and hydraulic interaction among the stations. By comparatively analyzing the results and making statistics on energy output characteristics, annual future contract energy of each station is determined and distributed to each month within a year. The major work of this dissertation is outlined as follows:
(1)After making statistics on the long-term runoff data of the upper Hanjiang River from 1954 to 1998, annual distribution, annual variation, intergenerational variation and high - low water change of runoff are analyzed. Spectral analysis and Kendall rank correlation coefficient test are adopted to analyze the periodicity and tendency of runoff data. The results show that the annual distribution and annual variation of runoff are uneven, and there is much difference between high and low, and small flow may appear in each month within a year, and the tendency of runoff is reduction.
(2)On the foundation of the main task of this cascade power stations and the influence of tariff, two models of maximizing energy output and maximizing energy benefit are respectively established, and DPSA and POA are combined to solve the models.
(3)Based on the analysis on runoff regularity of the upper Hanjiang River, one year is divided into 3 parts: wet season is from July to September, and dry season is December and from January to March, and the rest is normal season. The maximizing energy benefit model is solved based on the plans of different general tariff and different downward scales of wet season tariff. By making statistics on the ratios of energy output in the wet season to energy output in the dry season of calculation results, the plan is established, which general tariff is 0.2 Yuan per kilo-watt-hour, and downward scales of wet season tariff is thirty percent, and upward scales of dry season tariff is ninety percent.
(4)Comparing the calculation results of two models, it shows that energy output increases and abandoned water decreases by optimized operation. The average annual energy output calculated by maximizing energy benefit model is less than that calculated by maximizing energy output model, but the average annual energy benefit calculated by maximizing energy benefit model is more. As the result of the wet-dry seasonal tariff, energy output in dry season increases and that in wet season decreases. The structure of energy output component has pronounced changed and energy benefit in dry season account for an increasing proportion of annual energy benefit.
(5)According to the calculation results of long-term optimized operation and energy output statistics characteristics, plans of future contract energy are made. By comparing the proportion that future contract energy account for of annual energy output in different typical years, the future contract energy of each station account for forty-five percent of average annual energy output of each station. This plan has higher guaranteed efficiency.
(6)Future contract energy is distributed to each month within a year on the basis of reliable energy output in each month. The guaranteed efficiencies of Shiquan, Xihe and Ankang stations are eighty-five percent, eighty-five percent and ninety-five percent, which show that the future contract will be fulfilled in most of years.
引文
[1]裴哲义,韩放.水电与电力市场[J].水电自动化与大坝监测,2002,26(1):1-4.
[2]赵永龙,常晓青.电力市场模式下的水电调度探讨[J].中国电力,2000,33(11):62-64.
[3]王蕊,王丽萍,姜生斌等.西北电网水电参与市场化运营若干问题的研究[J].水力发电,2007,33(5):7-9.
[4]Arvanitidis,N.V and J.Rosing.Optimal Operation of multi-reservoir systems using a composite representation[C].IEEE.Transactions on Power apparatus and systems,Pas-89(2),1970.
[5]Turgeon,A.A decomposition method for the long-term scheduling of reservoir in series[J].Water Resources Research,1981,17(6):1565-1570.
[6]Turgeon,A..Optimal short-term hydro scheduling from the principle of progressive optimality[J].Water Resour.Research,1981,17(3):481-486.
[7]Turgeon,A.Optimal Short-Term Hydro Scheduling from the Principle of Progressive Optimality [J].Water Resources Research,1981,17(3):481-486.
[8]Foufoula E,Kitanidis P K.Gradient dynamic programming for stochastic optimal control of multi-dimensional water resources systems[J].Water Resources Research,1988,24(8):1345-1359.
[9]Karamouz M,Vasiliadis H V.Bayesian stochastic optimization of reservoir operating using uncertain forecast[J].Water Resources Research,1992,28(5):1221-1232.
[10]Oliveira R,Loucks D P.Operating rules for multi-reservoir systems[J].Water Resources Research,1997,33(4):839-852.
[11]Needham J.,Watkins D.,etc.Linear programming for flood control in the Iowa and Des Moines river[J].Journal of Water Resour.Plng.& Manag,2000,126(3):118-127.
[12]Peng C.S.and Buras N.,Practical estimation of inflow into multireservoir system[J].Journal of Water Resour.Plng.& Manag,2000,126(5):35-40.
[13]Barros M.,Tsai F.,etc.Optimization of Large-scale hydropower system operations[J].Journal of WaterResour.Plng.& Manag,,2003,129(3):178-188.
[14]V.Chandramouli and Paresh Deka.Neural network based decision support model for optimal reservoir operation[J].Water Resources Management,2005(19):447-464.
[15]D.Nagesh Komar and M.Janga Reddy.Ant colony optimization for multi-purpose reservoir operation[J].Water Resources Management,2006(20):879-898.
[16]Salvatore Barbagallo,etc.Discovering reservoir operation rules by a rough set approach[J].Water Resources Management,2006(20):19-36.
[17]Paulo Chaves and Toshiharu Kojiri.Stochastic fuzzy neural network:case study of optimal reservoir operation[J].Water Resources Planning and Management,2007,133(6):509-518.
[18]D.Nagesh Komar and M.Janga Reddy.Multipurpose reservoir operation using particle swarm optimization[J].Water Resources Planning and Management,2007,133(3):192-201.
[19]董子敖等.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[J].水电能源科学,1987,5(1):29-40.
[20]叶秉如等.红水河梯级优化调度的多次动态规划和空间分解算法[A].见:红水河水电最优开发数 学模型研究论文集[C].南京:河海大学,1998.
[21]胡振鹏,冯尚友.大系统多目标递阶分析“分解-聚合”方法[J].系统工程学报,1988,(1).
[22]李惕先等.水库电站群长期优化调度决策支持系统[R].国家“七五”重点科技项目报告,天津大学水力发电教研室,1990.
[23]胡铁松.水库调度智能决策支持系统理论与应用研究[D].武汉:武汉水利电力大学,1993.
[24]解建仓,田峰巍,黄强等.大系统分解协调算法在黄河干流水库联合调度中的应用[J].西安理工大学学报.1998,14(1):1-5.
[25]畅建霞,黄强,王义民.基于改进遗传算法的水电站水库优化调度[J].水力发电学报,2001,(3):85-90
[26]Wen-Cheng Huang,Lun-Chin Yuan,and Chi-Ming Lee.Linging genetic algorithms with stochastic dynamic programming to the long-term operation of a multi-reservoir system[J].Water Resources Research.2002,38(12):4-1-4-9.
[27]张双虎,黄强等.基于模拟遗传混合算法的梯级水库优化调度图制定[J].西安理工大学学报,2006,22(3):229-233.
[28]张双虎,黄强等.水电站水库优化调度的改进粒子群算法[J].水力发电学报,2007,26(1):1-5.
[29]陈健康,王黎,马光文.分时电价下水电站水库优化调度研究[J].四川大学学报(工程科学版),2000,32(6):1-3.
[30]丁军威,胡旸,夏清等.竞价上网中的水电优化运行[J].电力系统自动化,2002,2(3):19-23.
[31]马光文,王黎,过夏明.分时电价下多用途水库的运用方式研究[J].水科学进展,2002,13(5):583-586.
[32]陆洪升,欧述俊,杨关设.考虑峰谷电价的单-水电站水库的长期最优运行调度研究[J].中国农村水利水电,2003,(1):55-58.
[33]欧述俊.考虑峰谷电价的水库发电调度优化方法探讨[J].水力发电,2003,29(1):8-9,27.
[34]钟平安,王会容,李伟.市场机制下水电站实时优化调度分层耦合模型[J].水力发电,2003,29(6):12-15.
[35]蔡兴国,林士颖.电力市场中梯级水电站优化运行的研究[J].电网技术,2003,27(9):6-9.
[36]李承军,余昕卉等.分时电价下水电站群短期优化调度模型研究[J].水利水电技术,2005,36(7):116-119.
[37]刘学海,练继建,马超,万毅.基于市场竞价的梯级水电站群的实时优化运行研究[J].水利水电技术,2005,36(10):53-57.
[38]吴玮,周建中,曹广晶等.DSM分时电价下梯级水电站短期优化运营研究[J].水力发电,2005,31(7):17-19.
[39]纪昌明,张玉山,李继清.市场环境下水电系统厂间经济运行问题研究[J].华北电力大学学报,2005,32(1):99-102.
[40]谢红胜,华振兴等.市场机制下梯级水电站群短期优化调度模型研究[J].水电能源科学,2006,24(2):74-76,96.
[41]徐刚,马光文.计及电价风险的水电站短期优化调度[J].中国农村水利水电,2006,(11):91-92,95.
[42]刘治理,马光文,岳耀峰.电力市场下的梯级水电厂短期预发电计划研究[J].继电器,2006,34(4):46-48.
[43]李郁侠,赵军科,王伟.电力市场环境下水电站中长期运行优化调度[J].西安理工大学学报,2006,22(3).
[44]刘涵.水库优化调度新方法研究[D].西安:西安理工大学,2006.
[45]畅俊杰,高学军,赵昌瑞.洮河流域径流演变趋势分析[J].甘肃水利水电技术,2003,39(3):187-189.
[46]范钟秀.中长期水文预报[M].南京:河海大学出版社,1999:98-104.
[47]蒋晓辉.自然_人工二元模式下河川径流变化规律和合理描述方法研究[D].西安:西安理工大学,2002:36.
[48]邹斌,周浩,李晓刚.电力市场原理与实践[M].北京:中国林业出版社,北京大学出版社,2006.
[49]杜松怀.电力市场[M].北京:中国电力出版社,2004.
[50]任颖.电力市场基本理论及竞价交易模式综述[J].河南电力,2006(2):14-17.
[51]韩放等.电力市场的基本原则[J].电网技术,1995,19(9):51-54.
[52]姚建刚,章建,银车来.电力市场运营及其软件开发[M].北京:中国电力出版社,2002.
[53]刘秋华,韩愈.电力市场运营模式与市场结构研究[J].商业研究,2006(13):122-124.
[54]吴耀忠,安骏,倪彪.发电市场竞价模式解析[J].华东电力,2005,33(10):34-36.
[55]王锡凡,王秀丽,陈皓勇.电力市场基础[M].西安:西安交通大学出版社,2003.
[56]王锡凡,耿建.分段竞价与分时竞价的比较[J].电力系统自动化,2003,27(7):22-26
[57]Wang Xifan,Guan Xiaohong,Wang Xiuli.Block pricing for Electric Power Market[J].PES Review,2002,22(6):47-49.
[58]韩磊,王树一.电力市场电价理论及其实践[J].内蒙古电力技术,2001,19(3):4-6.
[59]王宏伟,刘开华,李红的.峰谷电价的作用与实施[J].电力系统及其自动化学报,1995,7(4):59-62.
[60]史连军,韩放.中国电力市场的现状与展望[J].电力系统自动化,2000(2):1-4.
[61]黄强,畅建霞.水资源系统多维临界调控的理论与方法[M].北京:中国水利水电出版社,2007.
[62]李郁侠.电力市场边际电价预测与水电厂竞价上网模式研究[D].西安:西安理工大学,2005.
[63]Watts D.,Rudnick H..Market Power and Competition in a Hydrothermal System[C].International Conference on Power System Technology,2002,3(10):1360-1365.
[64]畅建霞,黄强,王义民.水电站水库优化调度几种方法的讨论.水电能源科学,2002,18(3):19-22.
[65]刘子龙.水库确定性优化调度动态规划法模型及应用.人民长江,1999,30(10):46,48.
[66]黄强.水能利用.中国水利水电出版社,1996.
[67]Bellman,R.,and Dreyfus,S.Applied dynamic programming[M].New York:Elseviser,1970.
[68]宗航等.POA算法在梯级水电站短期优化调度中的应用.水电能源科学,2003,21(1):46-48.
[69]杨菊香.洮河梯级电站水库优化调度研究[D].西安:西安理工大学,2007.
[70]Yeh W.W-G.Reservoir Management and Operation Models:A State-of-the-Art Review[J].Water Resour.Res.,1985,21(12):1797-1818.
[71]冯尚友.水资源系统工程[M].武汉:湖北科学技术出版社,1991.
[72]董子敖.水库群调度与规划的优化理论和应用[M],济南:山东科学技术出版社,1989.
[73]胡运权.运筹学教程[M].北京:清华大学出版社,1998.
[74]雷霞,刘俊勇.四川省丰枯季节和峰谷分时电价状况的分析[J].电力技术经济,2006, 18(3):41-44.
[75]张维.制定发电厂峰谷电价和丰枯电价的探讨[J].华中电力,2004,17(2):42-44.
[76]王丽娟.基于电价的水库优化调度研究[D].武汉:武汉大学,2005.
[77]束洪春,董俊等.销售侧分行业实行丰枯丰谷分时电价初探[J].电力系统自动化,2006,30(14):36-40.
[78]刘昌,李继传等.峰谷分时电价的分析与建模[J].电力需求侧管理,2005,7(5):14-17.
[79]方红远,王浩,程吉林.初始轨迹对逐步优化算法收敛性的影响[J].水利学报,2002(11):27-30,37.
[80]黄强.石泉和喜河梯级水库联合调度研究[R].西安:西安理工大学,2007.
[81]李晓斌.汉江流域水库调度自动化系统可行性研究报告[R].西安:陕西省电力公司,2007.
[82]国家电力监管委员会.欧洲、澳洲电力市场[M].北京:中国电力出版社,2005.
[83]许俊巧,邹圣权,杨先贵.水电在湖北电力市场的运作探讨[J].湖北电力,2004,28(1):34-35.
[84]杨梅,王黎,杨道辉,马光文.电力期货与期权交易对水电商的风险规避作用[J].水力发电,2007,33(3):13-16.
[85]尚金成,黄永皓,夏清等.电力市场理论研究与应用[M].北京:中国电力出版社,2002.
[86]曾勇红,王锡凡.电力市场下水电厂竞价综述[J].电力自动化设备,2006,26(10):101-106.
[87]马莉,李英等.水电参与电力市场竞价的若干问题探讨[J].电力技术经济,2006,18(4).
[88]张森林.水电参与电力市场竞争若干问题研究(二)[J].水电能源科学,2006,24(3):62-65,78.
[89]郑彤.电力市场交易模式探讨[J].科技进步与对策,2003,(11):103-105.
[90]吴军,涂光瑜,罗毅等.电力市场交易方式分析[J].电力系统自动化,2002,26(12):24-29,34.
[91]R Bjorgan,C Liu,J Lawarree.Financial risk management in a competitive electricity market[J].IEEE Transactions on Power systems.1999,14(11):1285-1291.
[92]王丽萍.西北地区电力市场水电竞争交易研究[R]。西安:西北电网有限公司,2007.
[93]宋正强,侯志俭,王承民,杨辉玲.长期合约电量对电力市场价格影响的定量分析[J].继电器,2007,35(4):58-60,83.
[94]王雁凌,张粒子,舒隽,杨以涵.合同交易量和竞价交易量在日计划中的经济分配[J].电力系统自动化,2002,(5):45-48。
[95]宋依群,倪以信,候志俭,吴复力.基于均衡分析的总统调合同电量比例研究[J].中国电机工程学报,2004,24(7):64-67.
[96]张舒,王承民,何伟,候志俭.电力市场中期货与现货电量交易比例的研究[J].华东电力,2004,32(4):11-13.
[97]黎灿兵,胡亚杰,赵弘俊,李晓辉.合约电量分解通用模型与算法[J].电力系统自动化,2007,31(11):26-30.
[98]戴铁潮,张丹.确定性合约电量分解算法在浙江发电市场的应用[J].华东电力,2000(10):7-9.
[99]吴世勇,马光文,李辉.二滩水电站期货电量优化研究[J].水力发电学报,2006,25(2):99-102.
[100]韩亚萍.Visual Basic 6.0基础培训百例[M].北京:机械工业出版社,2006.
[2]赵永龙,常晓青.电力市场模式下的水电调度探讨[J].中国电力,2000,33(11):62-64.
[3]王蕊,王丽萍,姜生斌等.西北电网水电参与市场化运营若干问题的研究[J].水力发电,2007,33(5):7-9.
[4]Arvanitidis,N.V and J.Rosing.Optimal Operation of multi-reservoir systems using a composite representation[C].IEEE.Transactions on Power apparatus and systems,Pas-89(2),1970.
[5]Turgeon,A.A decomposition method for the long-term scheduling of reservoir in series[J].Water Resources Research,1981,17(6):1565-1570.
[6]Turgeon,A..Optimal short-term hydro scheduling from the principle of progressive optimality[J].Water Resour.Research,1981,17(3):481-486.
[7]Turgeon,A.Optimal Short-Term Hydro Scheduling from the Principle of Progressive Optimality [J].Water Resources Research,1981,17(3):481-486.
[8]Foufoula E,Kitanidis P K.Gradient dynamic programming for stochastic optimal control of multi-dimensional water resources systems[J].Water Resources Research,1988,24(8):1345-1359.
[9]Karamouz M,Vasiliadis H V.Bayesian stochastic optimization of reservoir operating using uncertain forecast[J].Water Resources Research,1992,28(5):1221-1232.
[10]Oliveira R,Loucks D P.Operating rules for multi-reservoir systems[J].Water Resources Research,1997,33(4):839-852.
[11]Needham J.,Watkins D.,etc.Linear programming for flood control in the Iowa and Des Moines river[J].Journal of Water Resour.Plng.& Manag,2000,126(3):118-127.
[12]Peng C.S.and Buras N.,Practical estimation of inflow into multireservoir system[J].Journal of Water Resour.Plng.& Manag,2000,126(5):35-40.
[13]Barros M.,Tsai F.,etc.Optimization of Large-scale hydropower system operations[J].Journal of WaterResour.Plng.& Manag,,2003,129(3):178-188.
[14]V.Chandramouli and Paresh Deka.Neural network based decision support model for optimal reservoir operation[J].Water Resources Management,2005(19):447-464.
[15]D.Nagesh Komar and M.Janga Reddy.Ant colony optimization for multi-purpose reservoir operation[J].Water Resources Management,2006(20):879-898.
[16]Salvatore Barbagallo,etc.Discovering reservoir operation rules by a rough set approach[J].Water Resources Management,2006(20):19-36.
[17]Paulo Chaves and Toshiharu Kojiri.Stochastic fuzzy neural network:case study of optimal reservoir operation[J].Water Resources Planning and Management,2007,133(6):509-518.
[18]D.Nagesh Komar and M.Janga Reddy.Multipurpose reservoir operation using particle swarm optimization[J].Water Resources Planning and Management,2007,133(3):192-201.
[19]董子敖等.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[J].水电能源科学,1987,5(1):29-40.
[20]叶秉如等.红水河梯级优化调度的多次动态规划和空间分解算法[A].见:红水河水电最优开发数 学模型研究论文集[C].南京:河海大学,1998.
[21]胡振鹏,冯尚友.大系统多目标递阶分析“分解-聚合”方法[J].系统工程学报,1988,(1).
[22]李惕先等.水库电站群长期优化调度决策支持系统[R].国家“七五”重点科技项目报告,天津大学水力发电教研室,1990.
[23]胡铁松.水库调度智能决策支持系统理论与应用研究[D].武汉:武汉水利电力大学,1993.
[24]解建仓,田峰巍,黄强等.大系统分解协调算法在黄河干流水库联合调度中的应用[J].西安理工大学学报.1998,14(1):1-5.
[25]畅建霞,黄强,王义民.基于改进遗传算法的水电站水库优化调度[J].水力发电学报,2001,(3):85-90
[26]Wen-Cheng Huang,Lun-Chin Yuan,and Chi-Ming Lee.Linging genetic algorithms with stochastic dynamic programming to the long-term operation of a multi-reservoir system[J].Water Resources Research.2002,38(12):4-1-4-9.
[27]张双虎,黄强等.基于模拟遗传混合算法的梯级水库优化调度图制定[J].西安理工大学学报,2006,22(3):229-233.
[28]张双虎,黄强等.水电站水库优化调度的改进粒子群算法[J].水力发电学报,2007,26(1):1-5.
[29]陈健康,王黎,马光文.分时电价下水电站水库优化调度研究[J].四川大学学报(工程科学版),2000,32(6):1-3.
[30]丁军威,胡旸,夏清等.竞价上网中的水电优化运行[J].电力系统自动化,2002,2(3):19-23.
[31]马光文,王黎,过夏明.分时电价下多用途水库的运用方式研究[J].水科学进展,2002,13(5):583-586.
[32]陆洪升,欧述俊,杨关设.考虑峰谷电价的单-水电站水库的长期最优运行调度研究[J].中国农村水利水电,2003,(1):55-58.
[33]欧述俊.考虑峰谷电价的水库发电调度优化方法探讨[J].水力发电,2003,29(1):8-9,27.
[34]钟平安,王会容,李伟.市场机制下水电站实时优化调度分层耦合模型[J].水力发电,2003,29(6):12-15.
[35]蔡兴国,林士颖.电力市场中梯级水电站优化运行的研究[J].电网技术,2003,27(9):6-9.
[36]李承军,余昕卉等.分时电价下水电站群短期优化调度模型研究[J].水利水电技术,2005,36(7):116-119.
[37]刘学海,练继建,马超,万毅.基于市场竞价的梯级水电站群的实时优化运行研究[J].水利水电技术,2005,36(10):53-57.
[38]吴玮,周建中,曹广晶等.DSM分时电价下梯级水电站短期优化运营研究[J].水力发电,2005,31(7):17-19.
[39]纪昌明,张玉山,李继清.市场环境下水电系统厂间经济运行问题研究[J].华北电力大学学报,2005,32(1):99-102.
[40]谢红胜,华振兴等.市场机制下梯级水电站群短期优化调度模型研究[J].水电能源科学,2006,24(2):74-76,96.
[41]徐刚,马光文.计及电价风险的水电站短期优化调度[J].中国农村水利水电,2006,(11):91-92,95.
[42]刘治理,马光文,岳耀峰.电力市场下的梯级水电厂短期预发电计划研究[J].继电器,2006,34(4):46-48.
[43]李郁侠,赵军科,王伟.电力市场环境下水电站中长期运行优化调度[J].西安理工大学学报,2006,22(3).
[44]刘涵.水库优化调度新方法研究[D].西安:西安理工大学,2006.
[45]畅俊杰,高学军,赵昌瑞.洮河流域径流演变趋势分析[J].甘肃水利水电技术,2003,39(3):187-189.
[46]范钟秀.中长期水文预报[M].南京:河海大学出版社,1999:98-104.
[47]蒋晓辉.自然_人工二元模式下河川径流变化规律和合理描述方法研究[D].西安:西安理工大学,2002:36.
[48]邹斌,周浩,李晓刚.电力市场原理与实践[M].北京:中国林业出版社,北京大学出版社,2006.
[49]杜松怀.电力市场[M].北京:中国电力出版社,2004.
[50]任颖.电力市场基本理论及竞价交易模式综述[J].河南电力,2006(2):14-17.
[51]韩放等.电力市场的基本原则[J].电网技术,1995,19(9):51-54.
[52]姚建刚,章建,银车来.电力市场运营及其软件开发[M].北京:中国电力出版社,2002.
[53]刘秋华,韩愈.电力市场运营模式与市场结构研究[J].商业研究,2006(13):122-124.
[54]吴耀忠,安骏,倪彪.发电市场竞价模式解析[J].华东电力,2005,33(10):34-36.
[55]王锡凡,王秀丽,陈皓勇.电力市场基础[M].西安:西安交通大学出版社,2003.
[56]王锡凡,耿建.分段竞价与分时竞价的比较[J].电力系统自动化,2003,27(7):22-26
[57]Wang Xifan,Guan Xiaohong,Wang Xiuli.Block pricing for Electric Power Market[J].PES Review,2002,22(6):47-49.
[58]韩磊,王树一.电力市场电价理论及其实践[J].内蒙古电力技术,2001,19(3):4-6.
[59]王宏伟,刘开华,李红的.峰谷电价的作用与实施[J].电力系统及其自动化学报,1995,7(4):59-62.
[60]史连军,韩放.中国电力市场的现状与展望[J].电力系统自动化,2000(2):1-4.
[61]黄强,畅建霞.水资源系统多维临界调控的理论与方法[M].北京:中国水利水电出版社,2007.
[62]李郁侠.电力市场边际电价预测与水电厂竞价上网模式研究[D].西安:西安理工大学,2005.
[63]Watts D.,Rudnick H..Market Power and Competition in a Hydrothermal System[C].International Conference on Power System Technology,2002,3(10):1360-1365.
[64]畅建霞,黄强,王义民.水电站水库优化调度几种方法的讨论.水电能源科学,2002,18(3):19-22.
[65]刘子龙.水库确定性优化调度动态规划法模型及应用.人民长江,1999,30(10):46,48.
[66]黄强.水能利用.中国水利水电出版社,1996.
[67]Bellman,R.,and Dreyfus,S.Applied dynamic programming[M].New York:Elseviser,1970.
[68]宗航等.POA算法在梯级水电站短期优化调度中的应用.水电能源科学,2003,21(1):46-48.
[69]杨菊香.洮河梯级电站水库优化调度研究[D].西安:西安理工大学,2007.
[70]Yeh W.W-G.Reservoir Management and Operation Models:A State-of-the-Art Review[J].Water Resour.Res.,1985,21(12):1797-1818.
[71]冯尚友.水资源系统工程[M].武汉:湖北科学技术出版社,1991.
[72]董子敖.水库群调度与规划的优化理论和应用[M],济南:山东科学技术出版社,1989.
[73]胡运权.运筹学教程[M].北京:清华大学出版社,1998.
[74]雷霞,刘俊勇.四川省丰枯季节和峰谷分时电价状况的分析[J].电力技术经济,2006, 18(3):41-44.
[75]张维.制定发电厂峰谷电价和丰枯电价的探讨[J].华中电力,2004,17(2):42-44.
[76]王丽娟.基于电价的水库优化调度研究[D].武汉:武汉大学,2005.
[77]束洪春,董俊等.销售侧分行业实行丰枯丰谷分时电价初探[J].电力系统自动化,2006,30(14):36-40.
[78]刘昌,李继传等.峰谷分时电价的分析与建模[J].电力需求侧管理,2005,7(5):14-17.
[79]方红远,王浩,程吉林.初始轨迹对逐步优化算法收敛性的影响[J].水利学报,2002(11):27-30,37.
[80]黄强.石泉和喜河梯级水库联合调度研究[R].西安:西安理工大学,2007.
[81]李晓斌.汉江流域水库调度自动化系统可行性研究报告[R].西安:陕西省电力公司,2007.
[82]国家电力监管委员会.欧洲、澳洲电力市场[M].北京:中国电力出版社,2005.
[83]许俊巧,邹圣权,杨先贵.水电在湖北电力市场的运作探讨[J].湖北电力,2004,28(1):34-35.
[84]杨梅,王黎,杨道辉,马光文.电力期货与期权交易对水电商的风险规避作用[J].水力发电,2007,33(3):13-16.
[85]尚金成,黄永皓,夏清等.电力市场理论研究与应用[M].北京:中国电力出版社,2002.
[86]曾勇红,王锡凡.电力市场下水电厂竞价综述[J].电力自动化设备,2006,26(10):101-106.
[87]马莉,李英等.水电参与电力市场竞价的若干问题探讨[J].电力技术经济,2006,18(4).
[88]张森林.水电参与电力市场竞争若干问题研究(二)[J].水电能源科学,2006,24(3):62-65,78.
[89]郑彤.电力市场交易模式探讨[J].科技进步与对策,2003,(11):103-105.
[90]吴军,涂光瑜,罗毅等.电力市场交易方式分析[J].电力系统自动化,2002,26(12):24-29,34.
[91]R Bjorgan,C Liu,J Lawarree.Financial risk management in a competitive electricity market[J].IEEE Transactions on Power systems.1999,14(11):1285-1291.
[92]王丽萍.西北地区电力市场水电竞争交易研究[R]。西安:西北电网有限公司,2007.
[93]宋正强,侯志俭,王承民,杨辉玲.长期合约电量对电力市场价格影响的定量分析[J].继电器,2007,35(4):58-60,83.
[94]王雁凌,张粒子,舒隽,杨以涵.合同交易量和竞价交易量在日计划中的经济分配[J].电力系统自动化,2002,(5):45-48。
[95]宋依群,倪以信,候志俭,吴复力.基于均衡分析的总统调合同电量比例研究[J].中国电机工程学报,2004,24(7):64-67.
[96]张舒,王承民,何伟,候志俭.电力市场中期货与现货电量交易比例的研究[J].华东电力,2004,32(4):11-13.
[97]黎灿兵,胡亚杰,赵弘俊,李晓辉.合约电量分解通用模型与算法[J].电力系统自动化,2007,31(11):26-30.
[98]戴铁潮,张丹.确定性合约电量分解算法在浙江发电市场的应用[J].华东电力,2000(10):7-9.
[99]吴世勇,马光文,李辉.二滩水电站期货电量优化研究[J].水力发电学报,2006,25(2):99-102.
[100]韩亚萍.Visual Basic 6.0基础培训百例[M].北京:机械工业出版社,2006.