智能工程在智能输电网规划不确定性问题建模中的应用
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摘要
摘要:近年来,为了应对资源和环境对电力系统发展提出的严峻挑战,电网智能化成为全球电网发展的必然趋势。随着能源结构的优化调整和清洁能源如风能、太阳能的快速发展、用户与电网之间的互动交互、新型市场参与方的出现,电力市场运营更加复杂,给输电网规划提出了新的要求,输电网规划面临更大的复杂性和不确定性。
     我国能源资源与需求逆向分布,需要依托智能电网技术进行大范围的资源优化配置,因此合理的智能输电网规划成为迫切需要研究的重大课题。面对新形势、新问题,本文从理论研究和工程应用出发,研究了综合的智能方法体系智能工程理论。从宏观政策、电网-用户互操作性、输电网扩展规划等不确定性方面探讨适用于智能输电网规划不确定性问题建模的方法学,主要研究工作如下:
     理论研究方面针对智能电网机制下输电网规划所面临的模糊随机、随机模糊等双重不确定性问题,对智能工程理论框架和方法体系进行发展和扩充。通过定义智能工程机会路径、交叉子空间、αβ-机会解等,扩充了智能工程优化理论并定义了协调优化算子、协同进化算子、目标冲突协调算子等,证明了相关定理,为应用智能工程理论进行智能输电网规划不确定性问题建模奠定了理论基础。
     智能电网建设是一项复杂巨系统工程,涉及国家政策、电力系统运行、不确定发电、不确定用电、实时电价等复杂性、不确定性问题。我国计划在2020年基本建成坚强智能电网,电网的资源配置能力、安全水平、运行效率以及电网与电厂、用户的互动水平显著提高。理论应用层面从协调智能电网各参与方利益入手,对智能输电网规划不确定性问题建模方法进行研究,抽取复杂的智能输电网规划不确定性问题如宏观政策模拟子问题、电网-用户互操作模拟子问题、电厂-电网-用户三方输电网协调规划子问题等三个子问题进行研究。
     针对三个子问题,本文应用智能工程理论分别对其进行理论研究与建模应用。运用智能工程混合模型、交互式协调机制对不确定性子问题进行建模,并在IEEE-39新英格兰节点测试系统和IEEE-30节点测试系统上模拟仿真,验证了智能工程方法学及智能工程混合协调模型解决不确定性问题的有效性。
ABSTRACT:In order to deal with the formidable challenges that resource and environment impact on power system's development, Smart Grid has become an inevitable trend on grid development around the world. With the optimization and revision in energy resource structure, rapid development of clean energies such as wind power and solar power, two-way communication between consumer and grid, emergence of new market participators, the electricity market operation becomes more and more complex, and it also raises new requirements to transmission planning, thus transmission planning is confronted with greater complexities and uncertainties.
     Energy resource is reversely distributed with energy demand in China, so smart grid technologies are indispensable for optimal resource allocation on wide area level, and reasonable smart transmission planning turns into an urgent and key task for research. Facing new situations and new issues, starting from theoretical research and engineering application, intensive researches on integrative intelligent methodology Intelligent Engineering (IE) are presented in this study. Applicable uncertainty problem's modeling in smart transmission planning methodology is explored from some uncertain perspectives, which consist of macroeconomic policy simulation, grid-consumer interoperability, transmission expansion planning, and so on. The main works are shown as follows:
     On theoretical research level, in view of dual uncertainties such as fuzzy random, random fuzzy emerge under smart grid mechanism, the theoretical framework and methodology of IE are pushed forward and expanded. IE chance path, sub-overlap space, αβ-chance solution are defined, IE optimization theory is expanded and coordinated optimization operator, co-evolution operator and objective-conflict coordination operator are created, and related theorems are proved. All above mentioned lay a solid foundation for uncertainty problems'modeling in smart transmission planning.
     Smart Grid's development is a complex giant system engineering, which involves complex and uncertain issues such as national policy, power system operation, uncertain generation, uncertain consumption, real time price, and so on. Strong&Smart Grid plan would be basically completed by2020in China, and by then resource allocation capacities, grid security and operation efficiency, interaction among generation, grid and consumer would be significantly enhanced. On theoretical application level, the methodology system of uncertainty problems of smart transmission planning is explored. The complicated uncertainty problems of smart transmission planning problem are divided into three And-subproblems i.e. macro policy simulation subproblem, grid-consumer interoperability simulation subproblem and generation-grid-consumer coordination planning subproblem for study.
     For the three And-subproblems, IE is partially employed for theoretical research and modeling practice in this study. IE hybrid model and interactive coordination are implemented to make uncertainty subproblem modeling, and simulations on IEEE-39bus test system and IEEE-30bus test system demonstrate the validity of IE methodology and coordinated IE hybrid model on solving uncertain problem.
引文
[1]KEVIN A B, TIM H, JONATHAN P. Navigating the Numbers:Greenhouse Gas Data and International Climate Policy. World Resources Institute,2005,12.
    [2]U.S. Department of Energy. "GRID 2030" a national vision for electricity's second 100 years [EB/OL]. [2011-03-07]. http://www.oe.energy.gov/DocumentsandMedia/Electric_Vision Document.pdf.
    [3]European Commission. European smartgrids technology platform:vision and strategy for Europe's electricity networks of the future[EB/OL]. [2009-03-15]. http://ec.europa.eu/-research/energy/pdf/smartgrids_en.pdf.
    [4]刘振亚.智能电网技术[M].北京:中国电力出版社,2010:1-16,101-325.
    [5]余贻鑫,栾文鹏.智能电网述评.中国电机工程学报,2009,29(34):1-8.
    [6]何光宇,孙英云,梅生伟,等.多指标自趋优的智能电网.电力系统自动化,2009,33(17):1-5.
    [7]王锡凡.电力系统优化规划.北京:水利电力出版社,1990:268-327.
    [8]程浩忠.电力系统规划[M].北京:中国电力出版社,2008:111-204.
    [9]杜松怀,温步瀛,蒋传文.电力市场.北京:中国电力出版社,2004.
    [10]张钦,王锡凡,付敏,等.需求响应视角下的智能电网.电力系统自动化,2009,33(17):49-55.
    [11]BELHOMME R, DEASUA R C R, VALTORTA G. ADDRESS-active demand for the smart grids of the future//Proceedings of CIRED Seminar 2008:Smart Grids for Distribution, June 23-24,2008, Frankfurt, Germany.
    [12]肖世杰.构建中国智能电网技术思考[J].电力系统自动化,2009,33(9):1-4.
    [13]Rahimi F, Ipakchi A. Demand response as a market resource under the smart grid paradigm. IEEE Transactions on Smart Grid,2010,1(1):82-88.
    [14]EPRI. TP-114660 Complex Interactive Networks/Systems Initiative:First Annual Report[EB/OL]. [2000-05-30]. http://my.epri.com/portal/server.pt?space=CommunityPag e&cached=true&parentname=ObjMgr&parentid=2&control=SetCommunity&CommunityID =404&RaiseDocID=TP-114660&RaiseDocType=Abstract_id.
    [15]http://www.gridwise.org/gridwisealli about.asp.
    [16]DOE. Smart grid system report[EB/OL]. [2009-07-07]. http://www.oe.energy.gov/Documen tsandMedia/SGSRMain 090707 lowres.pdf.
    [17]NIST. NIST Framework and Roadmap for Smart Grid Interoperability Standards [EB/OL]. [2010-01-19]. http://www.nist.gov/public_affairs/releases/upload/smartgrid_inte roperability_final.pdf.
    [18]http://www.smartgrids.eu/? q=node/27.
    [19]Green Paper:A European strategy for sustainable, competitive and secure energy [EB/OL]. [2006-03-08]. http://ec.eruopa.eu/energy/green-paper-energy/doc/2006_03_08_g p document en.pdf.
    [20]European Commission Community Research. European smartgrids technology platform: vision and strategy for Europe's electricity networks of the future [EB/OL]. http://ec.europa.eu/research/energy/pdf/smartgrids_en.pdf.
    [21]http://www.smartgrids.eu/documents/sra/sra_finalversion.pdf.
    [22]http://www.smartgrids.eu/documents/SmartGrids_SDD_FINAL_APRIL2010.pdf.
    [23]http://eur-lex.europa.eu/LexUriServ/LexUriServ.do?uri=COM:2010:0639:FIN:EN:PDF.
    [24]张怀宇.华东电网高级调度中心建设研究与实践.华东电网,2009,37(6):0891-0894.
    [25]郝悍勇.公司启动首批支撑智能电网信息化项目.国家电网报,[2009-10-13].
    [26]http://www.sgcc.com.cn/shouye/tbxw/196691.shtml.
    [27]http://www.csg.cn/news/compnewscon.aspx?id=17231&ItemCode=006002000000.
    [28]http://news.xinhuanet.com/politics/2010-03/05/content_13101906_1.htm.
    [29]樊铁钢,张勇传.电力市场中的不确定性.中国能源,1999,10:31-34.
    [30]金华征,程浩忠.电力市场下的电网灵活规划方法综述.电力系统及其自动化学报,2006,18(2):10-17.
    [31]胡兆光.电力视窗宏观调控实施效果分析[J].宏观经济研究.2005,(7):43-46.
    [32]盛硕.美国金融危机问题研究:演进、成因及启示[J].金融经济,2010,(16):56-59.
    [33]中华人民共和国国家统计局.2009中国统计年鉴.北京:中国统计出版社,2009.
    [34]中国电力企业联合会.2008年全国电力工业统计快报.http://www.cec.org.cn /tongjixinxibu/tongji/yuedushuju/.
    [35]张磊,王学亮.碳税开征在即,电力企业未雨绸缪.中国电力报,2011-03-10.
    [36]DOE. National Energy Technology Laboratory. Modern grid initiative:a vision for modern grid[EB/OL]. [2008-10-10]. http://www.netl.doe.gov/moderngrid/docs/.
    [37]Kreikebaum F, Das Debrup, Divan D. Reducing transmission investment to meet renewable portfolio standards using controlled energy flows. IEEE PES Conference on Innovative Smart Grid Technologies, Maryland, USA,2010.
    [38]胡兆光.中国特色的低碳经济、能源、电力之路初探.中国能源,2009,31(11):16-19.
    [39]中国气象局风能太阳能资源评估中心.中国陆地10米高度年平均风功率密度分布图,中国太阳能资源分布图[EB/OL]. http://cwera.cma.gov.cn/cn/.
    [40]EPRI. IntelliGrid:smart power for the 21st century[EB/OL]. http://my.epri.com/portal /server.pt?space=CommunityPage&cached=true &parentname=ObjMgr&parentid=2&control=SetCommunity&CommunityID=405.
    [41]http://www.supersmartgrid.net/.
    [42]http://www.whitehouse.gov/the-press-office/remarks-president-economy-wakarusa-indiana.
    [43]European Commission. Limiting global climate change to 2 degrees Celsius. The way ahead for 2020 and beyond. Communication from the Commission to the Council, the European Parliament, the European Economic and Social Committee and the Committee of the Regions. Brussels:European Commission; 2007.
    [44]Battaglini A, Lilliestam J, Haas A, et al. Development of SuperSmart Grids for a more efficient utilisation of electricity from renewable sources. Journal of Cleaner Production, 2009,7 (10):911-918.
    [45]http://www.supersmartgrid.net/about/.
    [46]CIRCE. http://www.circeproject.eu.
    [47]http://www.supersmartgrid.net/wp-content/uploads/2010/03/100-renewable_electricity-road map.pdf.
    [48]http://www.web2summit.com/web2008/.
    [49]http://jcwinnie.biz/wordpress/?p=4839.
    [50]国家电网公司.http://www.sgcc.com.cn/ywgk/yxxm/tgyjl/index.shtml.
    [51]南方电网公司.http://www.csg.cn/news/compnewscon.aspx?id=20025&ItemCode=0020020 00000.
    [52]国家电网公司.http://www.sgcc.com.cn/ywgk/jsxm/xstgyzl/index.shtml.
    [53]王静,杜燕飞.国家电网已制定出世界首个智能变电站系列技术标准.人民网,
    http://finance.people.com.cn/GB/168839/168861/220462/14548294.html. [2011-03-02]
    [54]王一.电力市场环境下的多目标输电网优化规划方法研究[学位论文].上海,上海交通大学,2008:1-6.
    [55]Kazerooni A K, Mutale J. Transmission network planning under security and environmental constraints. IEEE Transactions on Power System,2010,25(2):1169-1178.
    [56]陈启鑫,康重庆,夏清.低碳电力调度方式及其决策模型.电力系统自动化,2010,34(12):18-23.
    [57]MaghouliP, Hosseini S H, Buygi M O, et al. A multi-objective framework for transmission expansion planning in deregulated environments. IEEE Transactions Systems on Power System,2009,24(2):1051-1061.
    [58]刘宝锭,赵瑞清,王纲.不确定规划及应用.北京:清华大学出版社,2003:1-10,213-278.
    [59]孙洪波.电力网络规划[M].重庆:重庆大学出版社,1996:1-12,119-161.
    [60]付蓉,魏萍,万秋兰,等.市场环境下基于系统阻塞指标约束的多阶段输电网规划.继电器,2006,34(10):55-59,80.
    [61]王淳,欧阳年会.基于逐步倒推法的多阶段输电网络规划.电力科学与技术学报,2009,24(4):25-28.
    [62]Qiuxia Yu, Jianbo Guo, Xianzhong Duan. Dynamic multi-stage transmission network
    expansion Planning[C]. Proceedings of DRPT 2008, April 6-9, Nanjing, China.
    [63]谢敏,陈金富,段献忠,等.基于模糊阻塞管理的启发式电网规划方法.中国电机工程学报,2005,25(22):61-67.
    [64]武鹏,程浩忠,邢洁.基于可信性理论的输电网规划.电力系统自动化,2009,33(12):22-26.
    [65]Choi J, Tran T, EI-Keib A A, et al. A method for transmission system expansion planning considering probabilistic reliability criteria. IEEE Transactions on Power Systems,20(3): 1606-1615.
    [66]Yu H, Chung C Y, Wong K P. et al. A chance constrained transmission network expansion planning method with consideration of load and wind farm uncertainties. IEEE Transactions on Power Systems,2009,24(3):1568-1576.
    [67]刘思革,程浩忠,崔文佳.基于粗糙集理论的多目标电网规划最优化模型.中国电机工程学报,2007,27(7):65-69.
    [68]肖峻,罗凤章,王成山.一种基于区间分析的电网规划项目决策方法.电网技术,2004,28(7):62-67.
    [69]金华征,程浩忠,曾德君,等.基于集对分析的柔性电网规划方法.中国电机工程学报,2005,25(3):7-12.
    [70]张洪明,廖培鸿,仲建中.电网规划的灰色系统方法.电网技术,1995,19(12):19-23.
    [71]朱海峰,程浩忠,张焰,等.利用盲数进行电网规划的潮流计算方法.中国电机工程学报,2001,21(8):74-78.
    [72]程浩忠,朱海峰,王建民,等.基于盲数BM模型的电网灵活规划方法.上海交通大学学报,2003,37(9):1347-1350.
    [73]金华征,程浩忠,杨晓梅,等.基于联系数模型的电网灵活规划方法.中国电机工程学报,2006,26(12):16-20.
    [74]Bracken J, Gill J M M. Mathematical programs with optimization problems in the constraints [J]. Operations Research,1973,21:37-44.
    [75]黄伟.双层规划理论在电力系统中的应用研究[学位论文].杭州,浙江大学,2007:3-6.
    [76]范宏,程浩忠,金华征,等.考虑经济性可靠性的输电网二层规划模型及混合算法.中国电机工程学报,2008,28(16):1-7.
    [77]屈刚,程浩忠,马则良,等.考虑联络线传输功率的双层分区多目标输电网规划.中国电机工程学报,2009,29(31):40-46.
    [78]程浩忠,高赐威,马则良,等.多目标电网规划的分层最优化方法.中国电机工程学报,2003,23(10):11-16.
    [79]Maghouli P, Hosseini S H, Buygi M O, et al. A scenario-based multi-objective model for multi-stage transmission expansion planning. IEEE Transactions on Power Systems,2011, 26(1):470-478.
    [80]金华征,程浩忠,杨晓梅,等.模糊集对分析法应用于计及ATC的多目标电网规划.电力系统自动化,2005,29(21):45-49.
    [81]Sepasian M S, Seifi H, Foroud A A, et al. A multiyear security constrained hybrid generation-transmission expansion planning algorithm including fuel supply costs. IEEE Transactions on Power Systems,2009,24(3):1609-1618.
    [82]王淳,程浩忠.模拟植物生长算法及其在输电网规划中的应用.电力系统自动化,2007,31(7):24-28.
    [83]Bahiense L, Oliveira G C, Pereira M, et al. A mixed integer disjunctive model for transmission network expansion. IEEE Transactions on Power Systems,2001,16(3): 560-565.
    [84]Al-Hamouz Z M, Al-Faraj A S. Transmission expansion planning using nonlinear programming[C]. IEEE/PES Transmission and Distribution Conference and Exhibition 2002, Oct 6-10, Yokohama, Japan.50-55.
    [85]Braga A S D, Saraiva J S. A multiyear dynamic approach for transmission expansion planning and long-term marginal costs computation. IEEE Transactions on Power Systems, 2005,20(3):1631-1639.
    [86]Tor O B, Guven A N, Shahidehpour M. Congestion-driven transmission planning considering the impact of generator expansion. IEEE Transactions on Power Systems,2008,23(2): 781-789.
    [87]Rider M J, Garcia A V, Romero R. Transmission system expansion planning by a branch-and-bound algorithm. IET Generation, Transmission & Distribution,2008,2(1): 90-99.
    [88]Holland J H. Adaptation in natural and artificial systems[M]. Ann Arbor, MI:Univ. Michigan,1975.
    [89]Goldberg D E. Genetic algorithms in search, Optimization and machine learning. Boston: Addison-Wesley Longman Publishing Co. Inc.
    [90]Srinivas N, Deb K. Multi-objective optimization using nondominated sorting in genetic algorithms[J]. Evolutionary Computation,1994,2(3):221-248.
    [91]Deb K, Pratap A, Agarwal S, et al. A fast and elitist multiobjective genetic algorithm: NSGA-Ⅱ[J]. IEEE Transactions on Evolutionary Computation,2002,6(2):182-197.
    [92]Kirkpatrick S, Gelatt C D, Vecchi M P. Optimization by simulated annealing. Science, 1983,220,671-680.
    [93]陈小平,顾雪平.基于遗传模拟退火算法的负荷恢复计划制定.电工技术学报,2009,24(1):171-175,182.
    [94]卢莉蓉,行小帅,霍冰鹏.基于免疫规划的模拟退火算法.计算机工程,2007,33(19):196-198.
    [95]Glover F. Future paths for integer programming and links to artificial
    intelligence. Computers and Operations Research,13(5):533-549.
    [96]王赛一,王成山.遗传禁忌混合算法及其在电网规划中的应用.电力系统自动化,2004,28(20):43-46,62.
    [97]王春娟,张伏生,王帅,等.基于混合优化算法的电网规划方法.电网技术,2005,29(23):30-33,39.
    [98]Dorigo M. Optimization, learning and natural algorithms[D](in Italian). Milano:Politecnico di Milano.
    [99]Dorigo M, Gambardella L M. Ant colonies for the traveling salesman problem. BioSystems, 1997,43,73-81.
    [100]李生红,刘泽民,周正.ATM网上基于蚂蚁算法的VC路由选择方法.通信学报,2000,21(1):22-28.
    [101]陈根军,王磊,唐国庆.基于蚁群最优的输电网络扩展规划.电网技术,2001,25(6):21-24.
    [102]翟海保,程浩忠,吕干云.基于模式记忆并行蚁群算法的输电网规划.中国电机工程学报,2005,25(9):17-22.
    [103]Kennedy J, Eberhart R. Particle swarm optimization. Proceedings of IEEE International Conference on Nerual Networks, Nov 27-Dec 1, Perth, Australia.1942-1948.
    [104]陈海焱,陈金富,段献忠.含风电场电力系统经济调度的模糊建模及优化算法.电力系统自动化,2006,30(2):22-26.
    [105]金义雄,程浩忠,严健勇,等.基于局优分支优化的粒子群收敛保证算法及其在电网规划中的应用.中国电机工程学报,2005,25(23):12-18.
    [106]Farmer J D, Packard N H, Perelson A S. The immune system, adaptation, and machine learning[D]. Los Alamos:Loa Alamos National Laboratory,1986.187-204.
    [107]贺峰,熊信艮,吴耀武.改进免疫算法在电力系统电源规划中应用.电力自动化设备,2004,24(3):32-38.
    [108]唐铁英,邱家驹,蒙文川.免疫模糊算法在电网规划中的应用.浙江大学学报(工学版),2008,42(5):815-819.
    [109]唐铁英.人工免疫算法及其在电力系统规划中的应用研究[学位论文].杭州:浙江大学,2007.18-38.
    [110]Elmetwally M M, Aal F A, Awad M L, et al. A Hopfield neural network approach for integrated transmission network expansion planning. MEPCON 2008, EI-Minia, Egypt, Dec 19-Dec 21.371-376.
    [111]Gajbhiye R K, Naik Devang, Dambhare S, et al. An expert system approach for multi-year short-term transmission system expansion planning; an Indian experience. IEEE Transactions on Power Systems,2008,23(1):226-237.
    [112]徐敏杰.智能工程及其在电力供需分析与预警中的应用[学位论文].北京.北京交通大学,2008:13-28.
    [113]操龙兵,戴汝为.开放复杂智能系统.北京:人民邮电出版社,2008.
    [114]喻湘存,熊曙初.系统工程教程.北京:清华大学出版社,北京交通大学出版社,2006.
    [115][美]约翰H霍兰.隐秩序:适应性造就复杂性[M].周晓牧,韩晖,译.上海:上海科技教育出版社,2000:10-30.
    [116]胡兆光,方燕平.智能工程及其在电力发展规划中的应用.中国电机工程学报,2000,20(3):44-48.
    [117]胡兆光.电力经济智能模拟实验室研究.中国电力,2005,38(1):7-11.
    [118]胡兆光,单葆国.电力供需模拟试验——基于智能工程的软科学实验室.北京:中国电力出版社,2009.
    [119]Hu Zhaoguang. Intelligent engineering-Its application. SMC95 Canada.1995.
    [120]Hu Zhaoguang. Intelligent space. IEEE-Fuzzy99. South Korea,1999.
    [121]胡兆光.智能工程及其在电力经济模型中的应用.电网技术,1999,25(3):11-14.
    [122]李蒙,胡兆光.基于智能工程理论拓展的政策正向状态模拟新方法.中国电机工程学报,2006,26(25):31-36.
    [123]胡兆光,方燕平.智能工程与负荷预测.电网技术,1999,25(3):15-19.
    [124]胡兆光.电力经济智能模拟实验室研究.中国电力,2005,38(1):7-11.
    [125]胡兆光,谭显东,单葆国,等.智能工程与智能体在DSM补偿机制建模中的应用.中国电机工程学报,2008,28(13):125-131.
    [126]袁家海.电力经济发展关系研究-方法、实证与预测[学位论文].北京,华北电力大学,2006:116-121.
    [127]丁伟.市场机制下输电规划方法研究与投资分析[学位论文].北京,华北电力大学,2007:47-63.
    [128]焦晓佑.智能工程推理机制研究及其在电力供需平衡复杂性分析中的应用[学位论文].北京.北京交通大学,2008:15-26.
    [129]EPRI. Methodological approach for estimating the benefits and costs of smart grid demonstration[EB/OL]. [2010-01-26]. http://my.epri.com/portal/server.pt?Abstract i d=000000000001020342.
    [130]金鸿章,韦琦,郭健.复杂系统的脆性理论及应用.西安:西北工业大学出版社,2010:16-29.
    [131]Merrill H M, Wood A J. Risk and uncertainty in power system planning. International Journal of Electric Power & Energy Systems,1991,13(2):81-90.
    [132]刘宝锭,彭锦.不确定理论教程[M].北京:清华大学出版社,2005:21-128,177-231.
    [133]刘开第,吴和琴,庞彦军.不确定性信息数学处理及应用[M].北京:科学出版社,1999:1-13.
    [134]Silve I D J, Rider M J, Romero R, et al. Transmission network expansion planning considering uncertainty in demand. IEEE Transactions on Power System,2006,21(4): 1565-1573.
    [135]Yu H, Chung C Y, Wong K P, et al. A change constrained transmission network expansion planning method with consideration of load and wind farm uncertainties. IEEE Transactions on Power Systems,2009,24(3):1568-1576.
    [136]于晗,钟志勇,黄杰波,等.考虑负荷和风电出力不确定性的输电系统机会约束规划.电力系统自动化,2009,33(2),20-24.
    [137]王一,程浩忠,胡泽春,等.计及过负荷风险的输电网多目标期望值规划.中国电机工程学报,2009,29(1):21-27.
    [138]刘继春.电力市场运营系统.北京:中国电力出版社,2004:1-21,38-52.
    [139]张粒子,黄仁辉.智能电网对电力市场发展模式的影响与展望.电力系统自动化,2010,34(8):5-8,71.
    [140]鲁刚,魏玢,马莉.智能电网建设与电力市场发展.电力系统自动化,2010,34(9):
    1-6,22.
    [141]程浩忠,范宏,翟海保.输电网柔性规划研究综述·电力系统及其自动化学报,2007,
    19(1):21-27.
    [142]Kolmogorov A N. English translation 1950): Foundations of the theory of probabilitv. Berlin:Springer,1933. New York:Chelsea.
    [143]钱学森,子景元,戴汝为.一个科学的新领域——开放的复杂巨系统及其方法论.自然杂志,1990,13(1):3-10.
    [144]Wooldridge M. An Introduction of Multi-Agent System. John Wiley and Sons Ltd, 2001.20-145.
    [145]黄席越,向长城,殷礼胜.现代智能算法理论及应用.北京:科学出版社,2005.315-344.
    [146]毛新军.面向主体的软件开发.北京:清华大学出版社,2005.10-90.
    [147]史忠植.高级人工智能.北京:科学出版社,2006.290-305,408-475.
    [148]Conzelmann G, Boyd G, Koritarov V, et al. Multi-agent power market simulation using EMCAS. IEEE Power Engineering Society General Meeting,2005, June (3):2829-2834.
    [149]Hewitt C E. Offices are open systems. ACM Trans. Office Information Systems,1986, 4(3):271-287.
    [150]Weiss G, Dillenbourg P. What is multi in multiagent learning? Collaborative Learning, Cognitive and Computational Approaches. Amsterdam, Holland:Pergamon Press, 1998.64-80.
    [151]Maddox G P. A framework for distributed reinforcement learning. Adaptation and Learning in Multi-agent Systems. Springer-Verlag Berlin, Germany,1996:97-102.
    [152]Watkins C J C H, Dayan P. Technical report:Q-learning. Machine Learning,1992,8(3): 279-292.
    [153]Tsitsiklis, John N. Asynchronous stochastic approximation and Q-learning. Machine Learning,1994,16(3):185-202.
    [154]康重庆,江健健,夏清.基于智能个体信念学习的电力市场模拟的理论框架[J].电网技术,2005,29(12):10-15.
    [155]雷德明,严新平.多目标智能优化算法及其应用[M].北京:科学出版社,2009:36-104.
    [156]Carlos A, Coello C. A comprehensive survey of evolutionary-based multiobjective
    optimization techniques[J]. Knowledge and Information Systems,1999,1(3):269-308.
    [157]王秀丽,李淑慧,陈皓勇,等.基于非支配遗传算法及协同进化算法的多目标多区域电网规划.中国电机工程学报,2006,26(12):11-15.
    [158]Fonseca C M, Fleming P J. An overview of evolutionary algorithms in multi-objective optimization. Evolutionary Computation,1995,3(1):1-16.
    [159]周登勇,戴汝为.人工生命.模式识别与人工智能,1998,4(3):412-418.
    [160]Zhong Weicai, Liu Jing, Xue Mingzhi, et al. A multi-agent genetic algorithm for global numerical optimization. IEEE Transactions on System, Man and Cybernetics-Part B.2004, 34(2):1128-1141.
    [161]巩敦卫,孙晓燕.协同进化遗传算法理论及应用[M].北京:科学出版社,2009:17-59.
    [162]Back T, Eiben A E, Vandervaart N A L, et al. An empirical study on GA "without parameters". Proceedings of 6th Conference on Parallel Problem Solving from Nature, Berlin:Springer Verlag,2000:315-324.
    [163]胡兆光,单葆国,韩新阳,等.中国电力需求展望——基于电力供需研究实验室模拟实验.北京:中国电力出版社,2010:1-14,45-82.
    [164]中华人民共和国国家统计局.中华人民共和国2010年国民经济和社会发展统计公报.http://www.stats.gov.cn/tjgb/ndtjgb/qgndtjgb/t20110228_402705692.htm.
    [165]胡喜鹏.中国千万千瓦级风电基地盘点[N][2010-05-17].中国能源报,http://paper.people.com.cn/zgnyb/html/2010-05/17/content_518434.htm?div=-1.
    [166]杜燕飞.能源局:预计2015年我国太阳能发电装机将达1000万千瓦[N][2011-06-09].人民网-能源频道,http://energy.people.com.cn/GB/14861086.html.
    [167]谭显东.电力可计算一般均衡模型的构建及应用研究[学位论文].北京,华北电力大学,2008:25-49.
    [168]OdellJ. Agent technology green paper[M]. Massachusetts:Agent Working Group of OMG, 2000:8-14.
    [169]Chen Shuheng, Huang Yachi. Risk preference, forecasting accuracy and survival dynamics: simulations based on a multi-asset agent-based artificial stock market[J]. Journal of Economic Behavior & Organization,2008,67(3-4):702-717.
    [170]Parker D C, Filatova T. A conceptual design for a bilateral agent-based land market with heterogeneous economic agents [J]. Computers, Environment and Urban Systems,2008, 32(6):454-463.
    [171]Leigh Tesfatsion. Agent-based computational economics, growing economies from the bottom up[R/OL]. [2011-07-08]. http://www2.econ.iastate.edu/tesfatsi/ace.htm.
    [172]袁家海,丁伟,胡兆光.基于AGENT的计算经济学及其在电力市场理论中的应用综述[J].电网技术,2005,29(11):47-51.
    [173]宋依群.电力市场的多代理模型[J].中国电机工程学报,2005,25(8):80-83.
    [174]江健健,康重庆,夏清.电力市场模拟中的报价中标概率函数与发电商个体学习模型[J].电网技术,2005,29(13):26-31,39.
    [175]Gallego L, Duarte O, Delgadillo A. Strategic bidding in Colombian electricity market using a multi-agent learning approach [C]. Transmission and Distribution Conference and Exposition, Bogota, Colombia,2008.
    [176]袁家海,胡兆光.基于智能体的电力合约市场协商模拟系统[J].电网技术,2005,29(11):49-53,59.
    [177]康重庆,江健健,夏清.基于智能个体信念学习的电力市场模拟的理论框架[J].电网 技术,2005,29(12):10-15.
    [178]Jing Zhaoxia, Chen Haoyong. Ngan H W, et al. Effect of agent's action domain representation method in agent-based electricity market simulation[C]. Power and Energy Engineering Conference, Wuhan, China,2009.
    [179]Leigh Tesfatsion. Integrated Retail/Wholesale Power System Operations with Smart Grid Functionality:Project Homepage. [2011-07-09]. http://www2.econ.iastate.edu/tesfatsi/IRW ProjectHome.htm.
    [180]刘起运,陈璋,苏汝劫.投入产出分析[M].北京:中国人民大学出版社,2006:185-205.
    [181]田建伟,胡兆光,吴俊勇,等.基于多智能体建模的经济-电力动态模拟系统.中国电机工程学报,2010,30(7):85-91.
    [182]田建伟,胡兆光,吴俊勇,等.基于电力消费约束的投入产出表全象限动态外推方法.北京交通大学学报(社会科学版),2010,9(3):64-68.
    [183]胡兆光,段炜,肖潇,田建伟.基于ARE模型推导中国2010年投入产出表.能源技术经济,2011,23(11):8-14.
    [184]谭忠富,曹福成,王绵斌,等.供电公司实施可中断负荷的风险决策优化模型研究.中国电机工程学报,2005,25(25):129-134.
    [185]Federal Energy Regulatory Commission. Assessment of demand response & advanced metering [OB/OL]. [2010-03-20]. http://www.ferc.gov/legal/staff-reports/demand-response.pdf.
    [186]栾文鹏.高级量测体系.南方电网技术,2009,3(2):6-10.
    [187]赵鸿图,周京阳,于尔铿.支撑高效需求响应的高级量测体系.电网技术,2010,34(9):13-20.
    [188]Heidell J, Ware H. Is there a case for broadband utility communications networks? Valuing and Pricing incremental communications capacity on electric utility smart grid networks. The Electricity Journal,2010,23(1):21-33.
    [189]http://www.cpuc.ca.gov/PUC/energy/Demand+Response/ami.htm.
    [190]National Institute of Standards and Technology. NIST Framework and roadmap for smart grid interoperability standards, release 1.0[EB/OL]. http://www.nist.gov/public_affairs /releases/upload/smartgrid_interoperability_final.pdf.
    [191]Chao Hungpo. Price-responsive demand management for a smart grid world. The Electricity Journal,2010,23(1):7-20.
    [192]Newsham G R, Bowker B G. The effect of utility time-varying pricing and load control strategies on residential summer peak electricity use:a review. Energy Policy,2010,38(7): 3289-3296.
    [193]Centolella P. The integration of price responsive demand into regional transmission organization (RTO) wholesale power markets and system operations. Energy,2010,35(4): 1568-1574.
    [194]Wolak F A. Residential customer response to real-time pricing:the Anaheim critical-peak pricing experiment [EB/OL]. [2007-07-21]. http://econ.la.psu.edu/CAPCP/conferences/ anaheim_cpp_psu.pdf.
    [195]Schweppe F C, Caramanis M C, Tabors R D, et al. Spot pricing of electricity[M]. Boston, MA, USA:Kluwer Academic Publisher,1988.
    [196]Daryanian B, Bohn R E, Tabors R D. Optimal demand-side response to electricity spot prices for storage-type customers[J]. IEEE Transactions on Power Systems,1989,4(3):897-903.
    [197]Goldman C, Hopper N, Bharvirkar R. Customer strategies for responding to day-ahead market hourly electricity pricing. LBNL-57128,2005.
    [198]陈之栩,张粒子,舒隽.交直流迭代法求解含网损节点边际电价.电力系统自动化,2007,31(11):22-25.
    [199]Guille C, Gross G. A conceptual framework for the vehicle-to-grid(V2G) implementation. Energy Policy,2009,37(11):4379-4390.
    [200]Ota Y, Taniguchi H, Nakajima T, et al. An autonomous distributed vehicle-to-grid control of grid-connected electric vehicle//Proceedings of ICIIS 2009, Dec 28-31,2009, Kandy, SriLanka.
    [201]Venayagamoorthy G K, Mitra P, Corzine K, et al. Real-time modeling of distributed plug-in vehicles for V2G transactions//Proceedings of ECCE 2009, Sept 20-24,2009, San Jose, USA.
    [202]Alvarado F L, Jianping Meng, DeMarco C L, et al. Stability analysis of interconnected power systems coupled with market dynamics. IEEE Transactions on Power Systems,2001,16(4): 695-701.
    [203]Langer G. Poll:Traffic in the United States [EB/OL]. [2005-02-
    13]. http://abcnews.go.com/technology/traffic/story?id=485098&page=l.
    [204]殷树刚,张宇,拜克明.基于实时电价的智能用电系统.电网技术,2009,33(19):11-16.
    [205]胡兆光,韩新阳.综合资源战略规划与需求侧管理理论方法与实践[M].北京:中国电力出版社,2008.
    [206]周景宏,胡兆光,田建伟,等.电力综合资源战略规划模型与应用[J].电力系统自动化,2010,34(11):19-22,92.
    [207]孙宏斌,张伯明,吴文传,等.面向中国智能输电网的智能控制中心[J].电力科学与技术学报,2009,24(2):2-7.
    [208]杨德昌,李勇,Christian R,等.智能输电系统在中国的发展[J].电网技术,2010,34(5):1-6.
    [209]Kreikebaum F, Das Debrup, Divan D. Reducing transmission investment to meet renewable portfolio standards using controlled energy flows. IEEE PES Conference on Innovative Smart Grid Technologies, Maryland, USA,2010.
    [210]Bose A. Smart transmission grid applications and their supporting infrastructure[J]. IEEE Transactions on Smart Grid,2010,1(1):11-19.
    [211]徐敏杰,吴俊勇,胡兆光,等.电力市场环境下基于多智能体的多目标电网规划方法fJ].电力自动化设备,2008,28(1):33-37.
    [212]丁伟,胡兆光.智能工程理论扩展及其在电网规划中的应用[J].中国电机工程学报,2008,28(16):15-21.
    [213]何光宇,孙英云.智能电网基础[M].北京:中国电力出版社,2010:72-139.
    [214]St Clair H P. Practical concepts in capability and performance of transmission lines. AIEE Transactions,1953,72:1152-1157.
    [215]徐政.超、特高压交流输电系统的输送能力分析.电网技术,1995,19(8):7-12.
    [216]刘天琪.现代电力系统分析理论与方法[M].北京:中国电力出版社,2007:69-105.
    [217]Hingorani N G. High power electronics and flexible AC transmission system[J]. IEEE Power Engineering Review,1988,76(4):3-4.
    [218]张智刚,夏清.智能电网调度发电计划体系架构及关键技术[J].电网技术,2009,33(20):1-8.
    [219]陈皓勇,谭科,荆朝霞,等.电力市场综合模拟系统——实验方法与系统架构研究[J].电力自动化设备,2010,30(3):25-29.
    [220]刁勤华,林济铿,倪以信,等.博弈论及其在电力市场中的应用[J].电力系统自动化,2001,25(1):19-23.
    [221]康重庆,江健健,夏清.基于智能个体信念学习的电力市场模拟的理论框架[J].电网技术,2005,29(12):10-15.
    [222]刘梅招,杨莉,甘德强.基于Agent的电力市场仿真研究综述[J].电网技术,2005,29(4):76-80.
    [223]http://eblog.cersp.com/userlogl6/29980/archives/2007/540390.shtml.
    [224]田建伟,胡兆光,吴俊勇,等.远距离大容量风水互补系统的优化调度[J].北京交通大学学报(自然科学版),35(5):113-118.
    [225]New York Independent System Operator. Alternate route:electrifying the transportation sector, potential impacts of plug-in hybrid electric vehicles on New York state's electricity system[EB/OL]. [2010-07-05]. http://www.nyiso.com/public/webdocs/newsroom/press_rel eases/2009/Alternate_Route_NYISO_PHEV_Paper_062909.pdf.
    [226]KEMPTON W, LETENDRE S. Electric vehicles as a new power source for electric
    utilities[J]. Transportation Research (Part D),1997,2(3):157-175.
    [227]田建伟,胡兆光,周景宏,等.电网-用户互操作性对负荷曲线影响的定量模拟[J].电力系统自动化,2011,35(13):44-48.
    [228]Buygi M O. Market Based transmission expansion planning[J]. IEEE Transactions on Power System,2004,19(4):2060-2067.

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