智能电网规划与运行控制的柔性评价及分析方法
|
摘要
智能电网是人类社会应对资源紧缺、环境污染等一系列问题而提出的现代化电力供应系统。与传统电网相比，智能电网对电网规划、运行和管理的各个环节提出了更高的要求，要求电能生产、输送和消费的整个过程更加高效、经济和安全，同时具备更好的可操控性，提供更佳的用户体验。
在电力系统分析与计算中，通常以刚性约束的形式描述系统运行约束条件。一方面，这样的刚性描述方法过于刻板，很难满足智能电网对系统规划与运行管理灵活性的需求。另一方面，大量新技术的应用丰富了电力系统的控制手段，要求智能电网能够根据电网实际运行状态，灵活控制系统的各项运行参数。本文将工业过程系统设计中的柔性分析方法引入到电力系统分析与优化中，系统地提出智能电网规划与运行控制的柔性评价及分析方法。
本文所做的研究工作主要包括以下几方面：
1.在分析传统的电力系统优化模型中约束条件刚性表示方法不足的基础上，提出电力系统运行约束条件的柔性描述与分析方法；分析比较柔性分析方法与模糊集理论、概率理论，以及灰理论的区别；定义智能电网中的柔性概念，并对其进行分类描述；提出智能电网柔性评价的一维线性指标，并根据电网运行约束类型的不同，将该柔性评价指标从一维扩展至多维。
2.基于对最优潮流模型中等式和不等式约束条件的柔性化描述，进一步提出电网运行优化目标函数的柔性化表示方法，并将其转化为柔性等式约束的形式；兼顾电网运行的经济性、安全性与可靠性，建立智能电网经济调度的多维柔性综合优化模型，并提出模型求解方法。
3.将柔性分析方法应用于智能电网规划中，以柔性化方法评估整个电网规划周期内的投资成本、运行成本和可靠性收益；同时，通过对输电线路负载率约束的柔性化表示，在规划过程中保留部分系统输送能力，从而为系统预留一定的运行安全裕度和对不确定因素的适应能力。
4.根据输电线路实时动态热整定（RT-DTLR）系统的监测数据，确定输电线路的实时热稳定极限；通过对线路潮流约束进行柔性化表示，实现对线路潮流的灵活控制；将该技术与传统的电力系统切负荷策略相结合，综合考虑系统风险与收益，提出考虑RT-DTLR技术的智能电网柔性切负荷策略，并以满意度评价方法进行求解。
5.阐述智能电网中利用负荷柔性改善系统运行水平的实现方法；分析电动汽车作为智能电网中一类重要的柔性负荷，其充放电行为对电网运行的影响；研究智能电网对电动汽车充放电行为的引导与管理措施，分析电动汽车换电站的负荷柔性，通过对电动汽车换电站最优充放电策略的研究，求取电动汽车换电站的日负荷曲线，实现对其负荷的有序管理，并以此为依据分析换电站负荷对电网运行的影响。
6.提出电力系统运行均匀性分析与评估方法，在电网结构确定的情况下，分析系统运行均匀性与经济性和安全性之间的关系；从电力系统运行状态和安全裕度两个角度，定义系统状态均匀度和固有均匀度评估指标；针对固有均匀度指标直接求解的困难，利用本文提出的柔性分析方法，提出基于设备负载率柔性约束参数δ U和δ L的优化模型并进行求解。
本文以Garver6，IEEE14和IEEE30节点测试系统作为算例，分析和验证本文提出的智能电网规划与运行控制中柔性评价与分析方法的有效性。
Smart grid is a modern electric energy supply system to deal with a series of problems,such as resource shortage, environment pollution, etc., in human society. Compared withconventional power grids, smart grid sets much higher requirements on power gird planning,operation and management. The whole process of electric energy generation, transmission andcomsuption is required to be more efficient, economical and secure. Meanwhile, smart gridalso provides better controllability and user experiences.
In power system analysis and calculation, system operation constraints are usuallyexpressed in rigid forms. On one hand, such a rigid expression method appears to be tooinflexible to meet with the inquirements on flexibility of smart grid planning, operation andmanagement. On the other hand, with the large number of application of new technologies,control methods of power systems are greatly enriched. Smart grids are required to controlsystem operation parameters flexibly according to the actual grid operating states. Thisdissertation introduces flexibility analysis method in industry process system design to powersystem analysis and optimization, and systematacially proposes flexibility evaluation andanalysis method of smart grid planning and operation control.
Main research works and innovative points of this dissertation are as follows:
1. The disadvantages of rigid constraints in conventional power system analysis are firstanalyzed. Then, the concept of power system flexibility expression and analysis method isproposed and compared with fuzzy set theory, probability theory, and grey theory. After that,flexibility in smart grid analysis is defined and classified. A one-dimension linear index is proposed to evaluate smart grid flexibility. According to the different constraint types inpower system operation, it is then extended from one-dimension to multi-dimension.
2. Based on the flexible expression of equality and inequality constraints in optimalpower flow models, the flexible expression method of grid operation objective function isproposed. And the objective function is transferred to a flexible equality constraint. Then,taking grid operation economy, security and reliability into account, a multi-dimensionflexible comprehensive optimization model for smart grid economic dispatch is establishedand solved.
3. Flexibility analysis method is applied in smart grid planning. System investmentcosts, operation costs and reliability benefits are evaluated flexibly in the whole planningcycle. Meanwhile, through the flexible expression of transmission line load rate constraints,some system power flow transmission ability is reserved, so that a certain degree of systemoperation security margin and adaptability to uncertain factors can be reserved.
4. Based on the monitoring data from real-time dynamic thermal line rating (RT-DTLR)system, the real-time thermal stability limits of lines can be determined. Through the flexibleexpression of transmission line power flow constraints, line power flow can be controlledflexibly. Then, RT-DTLR technology is combined with conventional power system loadshedding strategies. Taking both system risks and benefits into account, a smart grid flexibleload shedding strategy involving RT-DTLR technology is established, and it is solved usingsatisfaction evaluation method.
5. The realization method of improving power system operation level by use of loadflexibility is first elaborated. Then, acting as an important kind of flexible load in smart grid,the effect of electric vehicle charging and discharging activities to power system operation isanalyzed. Based on the analysis of guidance and management measures of electric vehicles,the load characteristic of electric vehicle battery swapping station (EVBSS) can be obtained.After that, a model for optimal charging/discharging strategy of EVBSS is established and solved, so that the daily load curve of EVBSS can be obtained and the load of EVBSS can bemanaged orderly. Finally, base on the daily load curve obtained, the effect of EVBSS load onpower grid operation is analyzed.
6. Power system operation homogeneity analysis and evaluation method is proposed,and the relationship among system economy, security and homogeneity is analyzed. For theconsiderations of system operation states and security margins, degrees of power system statehomogeneity and inherent homogeneity are defined respectively. For the difficulties in directsolution of inherent homogeneity index, the flexibility analysis method proposed in thisdissertation is used. An optimal model based on flexible device load rate constraintparametersδ Uandδ Lis established and solved, so that the inherent homogeneity indexcan be obtained.
Garver6-bus, IEEE14-bus and IEEE30-bus test systems are used to analyze and verifythe validity of the flexibility evaluation and analysis method of smart grid planning andoperation control proposed in this dissertation.
在电力系统分析与计算中，通常以刚性约束的形式描述系统运行约束条件。一方面，这样的刚性描述方法过于刻板，很难满足智能电网对系统规划与运行管理灵活性的需求。另一方面，大量新技术的应用丰富了电力系统的控制手段，要求智能电网能够根据电网实际运行状态，灵活控制系统的各项运行参数。本文将工业过程系统设计中的柔性分析方法引入到电力系统分析与优化中，系统地提出智能电网规划与运行控制的柔性评价及分析方法。
本文所做的研究工作主要包括以下几方面：
1.在分析传统的电力系统优化模型中约束条件刚性表示方法不足的基础上，提出电力系统运行约束条件的柔性描述与分析方法；分析比较柔性分析方法与模糊集理论、概率理论，以及灰理论的区别；定义智能电网中的柔性概念，并对其进行分类描述；提出智能电网柔性评价的一维线性指标，并根据电网运行约束类型的不同，将该柔性评价指标从一维扩展至多维。
2.基于对最优潮流模型中等式和不等式约束条件的柔性化描述，进一步提出电网运行优化目标函数的柔性化表示方法，并将其转化为柔性等式约束的形式；兼顾电网运行的经济性、安全性与可靠性，建立智能电网经济调度的多维柔性综合优化模型，并提出模型求解方法。
3.将柔性分析方法应用于智能电网规划中，以柔性化方法评估整个电网规划周期内的投资成本、运行成本和可靠性收益；同时，通过对输电线路负载率约束的柔性化表示，在规划过程中保留部分系统输送能力，从而为系统预留一定的运行安全裕度和对不确定因素的适应能力。
4.根据输电线路实时动态热整定（RT-DTLR）系统的监测数据，确定输电线路的实时热稳定极限；通过对线路潮流约束进行柔性化表示，实现对线路潮流的灵活控制；将该技术与传统的电力系统切负荷策略相结合，综合考虑系统风险与收益，提出考虑RT-DTLR技术的智能电网柔性切负荷策略，并以满意度评价方法进行求解。
5.阐述智能电网中利用负荷柔性改善系统运行水平的实现方法；分析电动汽车作为智能电网中一类重要的柔性负荷，其充放电行为对电网运行的影响；研究智能电网对电动汽车充放电行为的引导与管理措施，分析电动汽车换电站的负荷柔性，通过对电动汽车换电站最优充放电策略的研究，求取电动汽车换电站的日负荷曲线，实现对其负荷的有序管理，并以此为依据分析换电站负荷对电网运行的影响。
6.提出电力系统运行均匀性分析与评估方法，在电网结构确定的情况下，分析系统运行均匀性与经济性和安全性之间的关系；从电力系统运行状态和安全裕度两个角度，定义系统状态均匀度和固有均匀度评估指标；针对固有均匀度指标直接求解的困难，利用本文提出的柔性分析方法，提出基于设备负载率柔性约束参数δ U和δ L的优化模型并进行求解。
本文以Garver6，IEEE14和IEEE30节点测试系统作为算例，分析和验证本文提出的智能电网规划与运行控制中柔性评价与分析方法的有效性。
Smart grid is a modern electric energy supply system to deal with a series of problems,such as resource shortage, environment pollution, etc., in human society. Compared withconventional power grids, smart grid sets much higher requirements on power gird planning,operation and management. The whole process of electric energy generation, transmission andcomsuption is required to be more efficient, economical and secure. Meanwhile, smart gridalso provides better controllability and user experiences.
In power system analysis and calculation, system operation constraints are usuallyexpressed in rigid forms. On one hand, such a rigid expression method appears to be tooinflexible to meet with the inquirements on flexibility of smart grid planning, operation andmanagement. On the other hand, with the large number of application of new technologies,control methods of power systems are greatly enriched. Smart grids are required to controlsystem operation parameters flexibly according to the actual grid operating states. Thisdissertation introduces flexibility analysis method in industry process system design to powersystem analysis and optimization, and systematacially proposes flexibility evaluation andanalysis method of smart grid planning and operation control.
Main research works and innovative points of this dissertation are as follows:
1. The disadvantages of rigid constraints in conventional power system analysis are firstanalyzed. Then, the concept of power system flexibility expression and analysis method isproposed and compared with fuzzy set theory, probability theory, and grey theory. After that,flexibility in smart grid analysis is defined and classified. A one-dimension linear index is proposed to evaluate smart grid flexibility. According to the different constraint types inpower system operation, it is then extended from one-dimension to multi-dimension.
2. Based on the flexible expression of equality and inequality constraints in optimalpower flow models, the flexible expression method of grid operation objective function isproposed. And the objective function is transferred to a flexible equality constraint. Then,taking grid operation economy, security and reliability into account, a multi-dimensionflexible comprehensive optimization model for smart grid economic dispatch is establishedand solved.
3. Flexibility analysis method is applied in smart grid planning. System investmentcosts, operation costs and reliability benefits are evaluated flexibly in the whole planningcycle. Meanwhile, through the flexible expression of transmission line load rate constraints,some system power flow transmission ability is reserved, so that a certain degree of systemoperation security margin and adaptability to uncertain factors can be reserved.
4. Based on the monitoring data from real-time dynamic thermal line rating (RT-DTLR)system, the real-time thermal stability limits of lines can be determined. Through the flexibleexpression of transmission line power flow constraints, line power flow can be controlledflexibly. Then, RT-DTLR technology is combined with conventional power system loadshedding strategies. Taking both system risks and benefits into account, a smart grid flexibleload shedding strategy involving RT-DTLR technology is established, and it is solved usingsatisfaction evaluation method.
5. The realization method of improving power system operation level by use of loadflexibility is first elaborated. Then, acting as an important kind of flexible load in smart grid,the effect of electric vehicle charging and discharging activities to power system operation isanalyzed. Based on the analysis of guidance and management measures of electric vehicles,the load characteristic of electric vehicle battery swapping station (EVBSS) can be obtained.After that, a model for optimal charging/discharging strategy of EVBSS is established and solved, so that the daily load curve of EVBSS can be obtained and the load of EVBSS can bemanaged orderly. Finally, base on the daily load curve obtained, the effect of EVBSS load onpower grid operation is analyzed.
6. Power system operation homogeneity analysis and evaluation method is proposed,and the relationship among system economy, security and homogeneity is analyzed. For theconsiderations of system operation states and security margins, degrees of power system statehomogeneity and inherent homogeneity are defined respectively. For the difficulties in directsolution of inherent homogeneity index, the flexibility analysis method proposed in thisdissertation is used. An optimal model based on flexible device load rate constraintparametersδ Uandδ Lis established and solved, so that the inherent homogeneity indexcan be obtained.
Garver6-bus, IEEE14-bus and IEEE30-bus test systems are used to analyze and verifythe validity of the flexibility evaluation and analysis method of smart grid planning andoperation control proposed in this dissertation.
引文
[1] Novosel D. Emerging technologies in support of smart grids [C]. IEEE PES General Meeting,Pittsburgh, USA,2008:1-2.
[2]张之哲,李兴源,程时杰.智能电网统一信息系统的框架、功能和实现[J].中国电机工程学报,2010,30(34):1-7.
[3]姚建国,严胜,杨胜春,等.中国特色智能调度的实践与展望[J].电力系统自动化,2009,33(17):16-20.
[4]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.
[5]陈树勇,宋书芳,李兰欣,等.智能电网技术综述[J].电网技术,2009,33(8):1-7.
[6]马其燕,秦立军.智能电网发展状况及其实现建议[J].电力需求侧管理,2010,12(3):34-37.
[7]余贻鑫,栾文鹏.智能电网述评[J].中国电机工程学报,2009,29(34):1-8.
[8]李同智.灵活互动智能用电的技术内涵及发展方向[J].电力系统自动化,2012,36(2):11-17.
[9]姚建国,赖业宁.智能电网的本质动因和技术需求[J].电力系统自动化,2010,34(2):1-5.
[10]白玉东.电力系统柔性分析与风电穿透功率极限研究[D].上海交通大学,2012.
[11] Grossmann I.E., Morari M. Operability, resiliency and flexibility—Process design objectives for achanging world [C]. In Proceedings of the2ndInternational Conference on Foundations ofComputer Aided Process and Design, Snowmass, USA,1983:931-1030.
[12] Ostrovsky G.M., Volin Yu.M., Barit E.I., et al. Flexibility analysis and optimization of chemicalplants with uncertain parameters [J]. Computers&Chemical Engineering,1994,18(8):755-767.
[13] Ostrovsky G.M., Volin Yu.M., Golovashkin D.V. Evaluation of chemical processes flexibility [J].Computers&Chemical Engineering,1996,20(S1): S617-S621.
[14]赵贺.电力电子在电力系统的应用--灵活交流输电系统[M].北京:中国电力出版社,2001.
[15]王海风,李敏,陈珩.统一潮流控制器的多变量控制设计[J].中国电机工程学报,2000,20(8):51-55.
[16]李红雨,雷万钧,卓放,等.大功率有源电力滤波器研究[J].电力电子技术,2004,38(2):13-15.
[17]李刚,程时杰,文劲宇,等.利用柔性功率调节器提高电力系统稳定性[J].中国电机工程学报,2006,12(26):1-6.
[18] Hingorani N.G. Network access and the future of power transmission [J]. EPRI Journal, April-May,1986:45-52.
[19]李家坤.柔性交流输电技术在电力系统中的应用[J].电力学报,2007,22(3):328-330.
[20]何大愚.柔性交流输电技术和用户电力技术的新进展[J].电力系统自动化,1999,23(6):8-13.
[21]朱海峰,程浩忠,张焰,等.电网灵活规划的研究进展[J].电力系统自动化,1999,23(17):38-41.
[22]程浩忠,阙讯,马则良,等.考虑出力调整和柔性约束的电网规划方法[J].上海交通大学学报,2005,39(3):417-420.
[23]程浩忠,张焰,严正,等.电力系统规划[M].北京:中国电力出版社,2008.
[24] Halemane K.P., Grossmann I.E.. Optimal process design under uncertainty [J]. AIChE Journal,1983,29(3):425-433.
[25] Swaney R.E., Grossmann I.E.. An index for operational flexibility in chemical process design, PartI: Formulation and theory [J]. AIChE Journal,1985,31(4):621-630.
[26]尹清华,江山,陈清林,等.过程系统的柔性分析和弹性设计研究进展与展望[J].炼油设计,2001,31(6):1-7.
[27] Swaney R.E., Grossmann I.E. An index for operational flexibility in chemical process design, PartII: Computational algorithms [J]. AIChE Journal,1985,31(4):631-641.
[28] Shimizu Y. A plain approach for dealing with flexibility problems in linear systems [J]. Computers&Chemical Engineering,1989,13(10):1189-1191.
[29] Varvarezos D.K., Grossmann I.E., Bieglar L.T. A sensitivity based approach for flexibility analysisand design of linear process systems [J]. Computer&Chemical Engineering,1995,19(12):1301-1316.
[30] Kazemi A., Badrzadeh B. Modeling and simulation of SVC and TCSC to study their limits onmaximum loadability point [J]. International Journal of Electrical Power&Energy Systems,2004,26(8):619-626.
[31]彭辉,樊庆玲,刘会金.配电网中TCSC和SVC的联合补偿[J].电力系统及其自动化学报,2002,14(4):16-18.
[32]王树文,纪延超,马文川.灵活交流输电技术[J].电力系统及其自动化学报,2007,19(3):113-117.
[33]李岩松,郭家骥,刘君.应用UPFC控制电力网络潮流的研究[J].电力系统及其自动化学报,2000,12(4):4-8.
[34] Hingorani N.G. FACTS and potential state-of-the-art: opportunities and limitations [C]. ICPST’94,1994, Oct. Beijing.
[35]徐瑞卿.基于盲数的市场环境下电网规划[D].北京交通大学,2007.
[36]金华征,程浩忠.电力市场下的电网灵活规划方法综述[J].电力系统及其自动化学报,2006,18(2):10-17.
[37] Van Geert E. Increased uncertainty a new challenge for power system planners [C]. IEEColloquium on Tools and Techniques for Dealing with Uncertainty, London, UK,1998:1/1-1/6.
[38]程浩忠,朱海峰,马则良,等.基于等微增率准则的电网灵活规划方法[J].上海交通大学学报,2003,37(9):1351-1353.
[39]朱海峰,程浩忠,张焰,等.考虑线路被选概率的电网灵活规划方法[J].电力系统自动化,2000,24(17):20-24.
[40]翟海保,程浩忠,陈春霖,等.基于最小期望悔值的电网灵活规划方法[J].上海交通大学学报,2005,39(9):27-30.
[41]高赐威,程浩忠,王旭.考虑场景发生概率的柔性约束电网规划模型[J].中国电机工程学报,2004,24(11):34-38.
[42] Gorenstin B.G., Campodonico N.M., Costa J.P., et al. Power system expansion planning underuncertainty [J]. IEEE Transactions on Power Systems,1993,8(1):129-136.
[43]张洪明,廖培鸿.输电网规划的灰色模型及算法[J].上海交通大学学报,1995,29(3):20-26.
[44]孙洪波.电力网络规划[M].重庆:重庆大学出版社,1996.
[45]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[J].上海交通大学学报,2003,37(9):1347-1350.
[46]高赐威,程浩忠,王旭.盲信息的模糊评价模型在电网规划中的应用[J].中国电机工程学报,2004,24(9):24-29.
[47]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[J].中国电机工程学报,2006,26(3):7-12.
[48]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[J].中国电机工程学报,2006,26(12):16-20.
[49] Binato S., Pereira M.V.F., Granville S. A new benders decomposition approach to solve powertransmission network design problems [J]. IEEE Transactions on Power Systems,2001,16(2):235-240.
[50] Bahiense L., Dliveira G.C., Pereira M., et al. A mixed integer disjunctive model for transmissionnetwork expansion [J]. IEEE Transactions on Power Systems,2001,16(3):560-565.
[51] Lee K.Y., Manuspiya S., Myeonsong Choi, et al. Network congestion assessment for short-termtransmission planning under deregulated environment [C]. Proceedings of2001IEEE PowerEngineering Society Transmission and Distribution Conference. Columbus, USA,2001,3:1266-1271.
[52] Kandi M.S., EI-Debeiky S.M., Hasanien N.E. A hybrid mathematical and rule-based system fortransmission network planning in a deregulated environment [C]. Proceedings of the IEEE PowerEngineering Society Summer Meeting. Vancouver, Canada,2001,1451-1456.
[53] Kit Po Wong, Yin Wa Wong. Combined genetic algorithm/simulated annealing/fuzzy set approachto short-term generation scheduling with take-or-pay fuel contract [J]. IEEE Transactions onPower Systems,1996,11(1):128-136.
[54] Da Silva E.L., Ortiz J.M.A., De Olivira G.C., et al. Transmission network expansion planningunder a Tabu search approach [J]. IEEE Transactions on Power Systems,2001,16(1):62-68.
[55]翟海保,程浩忠,吕干云,等.多阶段输电网络最优规划的并行蚁群算法[J].电力系统自动化,2004,28(20):37-42.
[56]胡家声,郭创新,叶彬,等.离散粒子群优化算法在输电网络扩展规划中的应用[J].电力系统自动化,2004,28(20):31-36.
[57] Galiana F.D., McGillis D.T., Marin M.A. Expert systems in transmission planning [J]. Proceedingsof the IEEE,1992,80(5):712-726.
[58]韩英铎,严干贵,姜齐荣,等.信息电力与FACTS及DFACTS技术[J].电力系统自动化,2000,24(19):1-7.
[59]韩民晓,肖湘宁,徐永海.柔性化供电技术[J].电力系统自动化,2002,26(8):1-5.
[60] Seki Tomomichi, Seki Toshibumi, Tanaka T, et a1. Flexible network integrated supervisorycontrol for power systems based on distributed objects [J]. Electrical Engineering in Japan,2001,136(4):34-46.
[61]杨海晶,张东英,吴琼,等.电力系统柔性SCADA框架设计及功能分析[J].电网技术,2006,30(15):36-39.
[62]杨海晶,杨以涵,马骞,等.基于IP技术的电力系统柔性SCADA研究与应用[J].继电器,2006,34(21):49-53.
[63]柳焯.最优化原理及其在电力系统中的应用[M].哈尔滨:哈尔滨工业大学出版社,1988.
[64]李彩华,郭志忠.最优潮流的发展[J].继电器,2002,30(1):1-6.
[65]张小平.电力系统潮流和最优潮流分析技术的进展专题简介[J].电力系统自动化,2005,29(16):1.
[66]孙伟卿,王承民,张焰,等.采用柔性化方法表示刚性约束的电力系统柔性优化模型[J].电网技术,2012,36(3):120-126.
[67] Browne J., Dubois D., Rathmill K., et al. Types of flexibility and classification of flexiblemanufacturing systems [J]. The FMS Magazine,1984,2(2):114-117.
[68] Sethi S.K., Sethi S.P. Flexibility in manufacturing: a survey [J]. International Journal of FlexibleManufacturing systems,1990,2:289-328.
[69]孙伟卿,王承民,张焰.智能化电网中的柔性评价方法与应用[J].电网与清洁能源,2011,27(5):5-11.
[70] Zadeh L.A. Fuzzy sets [J]. Information and Control,1965,8:338-353.
[71] Ma R., Yan H.W., Tong X.J. Multiobjective fuzzy optimal transaction planning based optimalpower flow for electricity market [C]. Proceedings of the7th International Power EngineeringConference, November29-December2,2005, Singapore:1-5.
[72] Ramesh V.C., Li X. A fuzzy multiobjective approach to contingency constrained OPF [J]. IEEETransactions on Power Systems,1997,12(3):1348-1354.
[73] Jaeseok C., El-Keib A.A., Tran T. A fuzzy branch and bound-based transmission system expansionplanning for the highest satisfaction level of the decision maker [J]. IEEE Transactions on PowerSystems,2005,20(1):476-484.
[74] Borkowska B. Probabilistic load flow [J]. IEEE Transactions on Power Apparatus and Systems,1974,93(3):752-759.
[75] Leite da Silva A.M., Ribeiro S.M.P., Arienti V.L., et al. Probabilistic load flow techniques appliedto power system expansion planning [J]. IEEE Transactions on Power Systems,1990,5(4):1047-1053.
[76]李雪,李渝曾,李海英.几种概率潮流算法的比较与分析[J].电力系统及其自动化学报,2009,21(3):12-17.
[77] Deng J.L. Control problems of Grey Systems [J]. Systems&Control Letters,1982,1(5):288-294.
[78]吴艳蕾.基于灰理论的居民生活电力消费预测研究[J].安徽工程科技学院学报,2008,23(1):32-34.
[79]姚力文,白小明,陈轶.基于灰理论的电力负荷预测模型[J].南昌大学学报（理科版）,2010,34(5):507-510.
[80] Kundur P., Paserba J., Ajjarapu V., et al. Definition and classification of power system stabilityIEEE/CIGRE joint task force on stability terms and definitions [J]. IEEE Transactions on PowerSystems,2004,19(3):1387-1401.
[81]“Demand-Side Management: The System Operator’s Perspective”, North American ElectricReliability Council (NERC), Princeton, NJ,1993.
[82]李来福,柳焯.需求侧管理在缓解紧急态势中的作用[J].电网技术,2008,32(7):56-60.
[83]张峰.电力负荷管理技术[M].北京:中国电力出版社,2005.
[84] Faranda R., Pievatolo A., Tironi E. Load shedding: a new proposal [J]. IEEE Transaction onPower Systems,2007,22(4):2086-2093.
[85] Concordia C., Fink L.H., Poullikkas G. Load shedding on an isolated system [J]. IEEETransactions on Power Systems,1995,10(3):1467-1472.
[86] Delfino B., Massucco S., Morini A., et al. Implementation and comparison of different underfrequency load-shedding schemes [C]. IEEE Summer Meeting2001, Vancouver, BC, Canada, Jul.15-19,2001,1:307-312.
[87] Ding X., Girgis A.A. Optimal load shedding strategy in power systems with distributed generation[C]. IEEE Power Engineering Society Winter Meeting, Columbus, OH, Feb.2001,2:788-793.
[88]申景双,蒋传文,侯志俭.发电机组超铭牌出力时经济补偿的研究[J].华东电力,2002,30(10):9-10.
[89]中国国家标准化管理委员会. GB/T12325-2008电能质量供电电压偏差[S].北京：中国标准出版社,2008.
[90]叶鸿声,龚大卫,黄伟中.提高导线允许温度增加线路输送容量的研究及在500kV线路上的应用[J].华东电力,2006,34(8):43-46.
[91]陈芳,韩学山,康凯,等.基于SCADA信息追踪输电线路动态热定值[J].电力系统自动化,2010,34(5):81-85.
[92]程浩忠,范宏,翟海保.输电网柔性规划研究综述[J].电力系统及其自动化学报,2007,19(1):21-27.
[93] Cruz-Rodriguez R.D., Latorre-Bayona G. HIPER: interactive tool for mid-term transmissionexpansion planning in a deregulated environment [J]. IEEE Power Engineering Review,2000,20(21):61-62.
[94]袁越,吴博文,李振杰,等.基于多场景概率的含大型风电场的输电网柔性规划[J].电力自动化设备,2009,29(10):8-12.
[95]曾鸣,吕春泉,邱柳青,等.风电并网时基于需求侧响应的输电规划模型[J].电网技术,2011,35(4):129-134.
[96]周金辉,余贻鑫,曾沅.大规模风电接入下输电网扩展规划的启发式优化算法[J].电力系统自动化,2011,35(22):66-70.
[97] Zhao J.H., Foster J., Dong Z.Y., et al. Flexible transmission network planning consideringdistributed generation impacts [J]. IEEE Transactions on Power Systems,2011,26(3):1434-1443.
[98]郑静,文福拴,李力,等.计及风险控制策略的含风电机组的输电系统规划[J].电力系统自动化,2011,35(22):71-76.
[99]白玉东,王承民,衣涛,等.基于柔性分析的风电并网容量优化建模[J].电力系统自动化,2012,36(12):17-24.
[100]白玉东,王承民,衣涛,等.电力系统的柔性评价与风电穿透功率极限计算[J].电力自动化设备,2012,32(10):12-16.
[101]黄德才,赵克勤.用联系数描述和处理网络计划中的不确定性[J].系统工程学报,1999,14(2):112-117.
[102]武鹏.考虑不确定因素的输电网灵活规划方法研究[D].上海交通大学,2009.
[103]于群,曹娜,郭剑波.负载率对电力系统自组织临界状态的影响分析[J].电力系统自动化,2012,36(1):24-27.
[104]常康,韩学山,王孟夏,等.电网关键元件及其单调性研究I：概念与基础[J].电力系统保护与控制,2009,37(6):1-5.
[105]梁才,刘文颖,温志伟,等.电网组织结构对其自组织临界性的影响[J].电力系统保护与控制,2010,38(20):6-11.
[106]赵书强,王磊.改进蚁群算法在配电网规划中的应用电力系统保护与控制[J].电力系统保护与控制,2010,38(24):61-65.
[107]Romero R., Monticelli A., Garcia A., et al. Test systems and mathematical models fortransmission network expansion planning [J]．IEE Proceedings–Generation, Transmission&Distribution,2002,149(1):27-36.
[108]Li F.X., Qiao W., Sun H.B., et al. Smart transmission grid: vision and framework [J]. IEEETransactions on Smart Grid,2010,1(2):168-177.
[109]Jabr R.A, Coonick A.H., Cory B.J. A homogeneous linear programming algorithm for the securityconstrained economic dispatch problem [J]. IEEE Transactions on Power Systems,2000,15(3):930-936.
[110]Henke R.K., Sciacca S.C. Dynamic thermal rating of critical lines-a study of real-time interfacerequirements [J]. IEEE Computer Applications in Power,1989,2(3):46-51.
[111]Foss S.D., Maraio R.A. Dynamic line rating in the operating environment [J]. IEEE Transactionson Power Delivery,1990,5(2):1095-1105.
[112]Seppa T.O. Increasing transmission capacity by real time monitoring [J]. IEEE Power EngineeringSociety Winter Meeting,2002,2:1208-1211.
[113]Wiszniewski A. New criteria of voltage instability margin for the purpose of load shedding [J].IEEE Transactions on Power Delivery,2007,22(3):1367-1371.
[114]Wan H., McCalley J.D., Vittal, V. Increasing thermal rating by risk analysis [J]. IEEETransactions on Power Systems,1999,14(3):815-828.
[115]Musilek P., Heckenbergerova J., Bhuiyan M.M.I. Spatial analysis of thermal aging of overheadtransmission conductors [J]. IEEE Transactions on Power Delivery,2012,27(3):1196-1204.
[116]Kim D.M., Kim J.O. Prediction of transmission-line rating based on thermal overload probabilityusing weather models [J]. European Transactions on Electrical Power,2010,20(4):534-544.
[117]Hosek J., Musilek P., Lozowski E., et al. Effect of time resolution of meteorological inputs ondynamic thermal rating calculations [J]. IET Generation, Transmission&Distribution,2011,5(9):941-947.
[118]Saied M.M. Assessing the dynamic rating of overhead transmission lines [J]. EuropeanTransactions on Electrical Power,2007,17(5):526-536.
[119]Heckenbergerova J., Musilek P., Filimonenkov K. Quantification of gains and risks of staticthermal rating based on typical meteorological year [J]. International Journal of Electrical Power&Energy Systems,2013,44(1):227-235.
[120]王益民.坚强智能电网技术标准体系研究框架[J].电力系统自动化,2010,34(22):1-6.
[121]Hur K., Boddeti M., Sarma N.D.R., et al. High-wire act [J]. IEEE Power and Energy Magazine,2010,8(1):37-45.
[122]Albizu I., Fernandez E., Mazon A.J., et al. Influence of the conductor temperature error on theoverhead line ampacity monitoring systems [J]. IET Generation, Transmission&Distribution,2011,5(4):440-447.
[123]Siwy E. Risk analysis in dynamic thermal overhead line rating [C]. International Conference onProbabilistic Methods Applied to Power Systems, Stockholm, Sweden, June2006:1-5.
[124]Chu R.F. On selecting transmission lines for dynamic thermal line rating system implementation[J]. IEEE Transactions on Power Systems,1992,7(2):612-619.
[125]Ahmed M.A.H., Azah M., Aini H. Vulnerability control of large scale interconnected powersystem using neuro-fuzzy load shedding approach [J]. Expert System with Applications,2010,37(4):3171-3176.
[126]Wang Y., Pordanjani I.R., Li W., et al. Strategy to minimise the load shedding amount for voltagecollapse prevention [J]. IET Generation, Transmission&Distribution,2011,5(3):307-313.
[127]Ghaleh A.P., Sanaye-Pasand M., Saffarian A. Power system stability enhancement using a newcombinational load-shedding algorithm [J] IET Generation, Transmission&Distribution,2011,5(5):551-560.
[128]Varadarajan M., Swarup K.S. Solving multi-objective optimal power flow using differentialevolution [J]. IET Generation, Transmission&Distribution,2008,2(5):720-730.
[129]Sun D.I., Ashley B., Brewer B., et al. Optimal power flow by Newton approach [J]. IEEETransactions on Power Apparatus and Systems,1984,103(10):2864-2880.
[130]滕乐天.电动汽车充电机（站）设计[M].北京:中国电力出版社,2009.
[131]高赐威,张亮.电动汽车充电对电网影响的综述[J].电网技术,2011,35(2):127-131.
[132]徐立中,杨光亚,许昭,等.电动汽车充电负荷对丹麦配电系统的影响[J].电力系统自动化,2011,35(14):18-23.
[133]Fernández L.P., Román T.G.S., Cossent R., et al. Assessment of the Impact of Plug-in ElectricVehicles on Distribution Networks [J]. IEEE Transactions on Power Systems,2011,26(1):206-213.
[134]鲍冠南,陆超,袁志昌,等.基于动态规划的电池储能系统削峰填谷实时优化[J].电力系统自动化,2012,36(12):11-16.
[135]赵俊华,文福拴,杨爱民,等.电动汽车对电力系统的影响及其调度与控制问题[J].电力系统自动化,2011,35(14):2-10.
[136]胡泽春,宋永华,徐智威,等.电动汽车接入电网的影响与利用[J].中国电机工程学报,2012,32(4):1-10.
[137]徐智威,胡泽春,宋永华,等.充电站内电动汽车有序充电策略[J].电力系统自动化,2012,36(11):38-43.
[138]姚伟锋,赵俊华,文福拴,等.基于双层优化的电动汽车充放电调度策略[J].电力系统自动化,2012,36(11):30-37.
[139]张舒,胡泽春,宋永华,等.考虑电动汽车换电站与电网互动的机组组合问题研究[J].中国电机工程学报,2012,32(10):49-55.
[140]Clement K, Haesen E, Driesen J. The impact of charging plug-in hybrid electric vehicles on aresidential distribution grid [J]. IEEE Transactions on Power Systems,2010,25(1):371-380.
[141]王丹,龙亮,葛琪,等.基于低谷填入法的插电式混合动力汽车集中充电策略[J].电力需求侧管理,2010,12(6):8-11.
[142]康继光,卫振林,程丹明,等.电动汽车充电模式与充电站建设研究[J].电力需求侧管理,2009(5):64-66.
[143]岳思,李艳.电动汽车充电模式及方式浅析[J].通信电源技术,2012,29(2):38-40.
[144]刘晓飞,张千帆,崔淑梅.电动汽车V2G技术综述[J].电工技术学报,2012,27(2):121-127.
[145]Ota Y., Taniguchi H., Nakajima T., et al. An autonomous distributed vehicle-to-grid control ofgrid-connected electric vehicle [C]. Industrial and Information Systems (ICIIS),2009:414-418.
[146]Saber A.Y., Venayagamoorthy G.K. Unit commitment with vehicle-to-grid using particle swarmoptimization [C]. IEEE Bucharest Power Tech,2009:1-8.
[147]薛飞,雷宪章,张野飚,等.电动汽车与智能电网从V2G到B2G的全新结合模式[J].电网技术,2012,36(2):29-34.
[148]薛晨,黎灿兵,曹一家,等.智能电网中的电网友好技术概述及展望[J].电力系统自动化,2011,35(15):102-107.
[149]王蓓蓓,李扬,高赐威.智能电网框架下的需求侧管理展望与思考[J].电力系统自动化,2009,33(20):17-22.
[150]Moghaddam M.P., Baboli P.T., Alishahi E, et al. Flexible load following the wind powergeneration [C]. IEEE International Energy Conference and Exhibition (EnergyCon),2010:802-807.
[151]孙伟卿,王承民,张焰.智能电网中的柔性负荷[J].电力需求侧管理,2012,14(3):10-13.
[152]曹一家,谭益,黎灿兵,等.具有反向放电能力的电动汽车充电设施入网典型方案[J].电力系统自动化,2011,35(14):48-52.
[153]徐丙垠,李天友,薛永端.智能配电网与配电自动化[J].电力系统自动化,2009,33(17):38-41.
[154]李燕.负荷的削峰填谷与电网的经济运行[J].电工电气,2011,5:42-44.
[155]殷树刚,苗文静,拜克明.准实时电价策略探析[J].电力需求侧管理,2011,13(1):20-23.
[156]罗卓伟,胡泽春,宋永华,等.大规模电动汽车充放电优化控制及容量效益分析[J].电力系统自动化,2012,36(10):19-26.
[157]段登伟,刘俊勇,吴集光.计及风险的配电公司最优分时零售电价模型[J].电力系统自动化,2005,29(3):8-12.
[158]Zhang W.J., Li F.X., Tolbert L.M. Review of reactive power planning: objectives, constraints, andalgorithms [J]. IEEE Transactions on Power Systems,2007,22(4):2177-2186.
[159]孙伟卿,王承民,张焰,等.基于Pareto最优的电力系统有功－无功综合优化[J].电力系统自动化,2009,33(10):38-42.
[160]郑晓,张静,马韬韬,等.基于改进决策方法的电力系统多目标优化调度[J].电工技术学报,2010,25(9):151-156.
[161]韩学山,赵建国.刚性优化与柔性决策结合的电力系统运行调度理论探讨[J].中国电力,2004,37(1):15-18.
[162]张强,韩学山,徐建政.安全经济调度与均匀调度间关系分析[J].电力系统及其自动化学报,2005,17(2):84-89.
[163]常康,韩学山,王孟夏,等.电网关键元件及其单调性研究I：概念与基础[J].电力系统保护与控制,2009,37(6):1-5.
[164]梁才,刘文颖,温志伟,等.电网组织结构对其自组织临界性的影响[J].电力系统保护与控制,2010,38(20):6-11.
[165]史进,涂光瑜,罗毅.电力系统复杂网络特性分析与模型改进[J].中国电机工程学报,2008,28(25):93-98.
[166]徐林,王秀丽,王锡凡.使用等值导纳进行电力系统小世界特性识别[J].中国电机工程学报,2009,29(19):20-26.
[167]赵鸿图,朱治中,于尔铿.电力市场中需求响应市场与需求响应项目研究[J].电网技术,2010,34(5):146-153.
[168]曾鸣,张艳馥,王鹤,等.基于综合资源规划的供需资源优化组合模型[J].电力系统自动化,2007,31(3):24-28.
[169]王蓓蓓,李扬.面向智能电网的电力需求侧管理规划及实施机制[J].电力自动化设备,2010,30(12):19-24.
[170]Wang H., Murillo-Sanchez C.E., Zimmerman R.D., et al. On computational issues ofmarket-based optimal power flow [J]. IEEE Transactions on Power Systems,2007,22(3):1185-1193.
[2]张之哲,李兴源,程时杰.智能电网统一信息系统的框架、功能和实现[J].中国电机工程学报,2010,30(34):1-7.
[3]姚建国,严胜,杨胜春,等.中国特色智能调度的实践与展望[J].电力系统自动化,2009,33(17):16-20.
[4]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.
[5]陈树勇,宋书芳,李兰欣,等.智能电网技术综述[J].电网技术,2009,33(8):1-7.
[6]马其燕,秦立军.智能电网发展状况及其实现建议[J].电力需求侧管理,2010,12(3):34-37.
[7]余贻鑫,栾文鹏.智能电网述评[J].中国电机工程学报,2009,29(34):1-8.
[8]李同智.灵活互动智能用电的技术内涵及发展方向[J].电力系统自动化,2012,36(2):11-17.
[9]姚建国,赖业宁.智能电网的本质动因和技术需求[J].电力系统自动化,2010,34(2):1-5.
[10]白玉东.电力系统柔性分析与风电穿透功率极限研究[D].上海交通大学,2012.
[11] Grossmann I.E., Morari M. Operability, resiliency and flexibility—Process design objectives for achanging world [C]. In Proceedings of the2ndInternational Conference on Foundations ofComputer Aided Process and Design, Snowmass, USA,1983:931-1030.
[12] Ostrovsky G.M., Volin Yu.M., Barit E.I., et al. Flexibility analysis and optimization of chemicalplants with uncertain parameters [J]. Computers&Chemical Engineering,1994,18(8):755-767.
[13] Ostrovsky G.M., Volin Yu.M., Golovashkin D.V. Evaluation of chemical processes flexibility [J].Computers&Chemical Engineering,1996,20(S1): S617-S621.
[14]赵贺.电力电子在电力系统的应用--灵活交流输电系统[M].北京:中国电力出版社,2001.
[15]王海风,李敏,陈珩.统一潮流控制器的多变量控制设计[J].中国电机工程学报,2000,20(8):51-55.
[16]李红雨,雷万钧,卓放,等.大功率有源电力滤波器研究[J].电力电子技术,2004,38(2):13-15.
[17]李刚,程时杰,文劲宇,等.利用柔性功率调节器提高电力系统稳定性[J].中国电机工程学报,2006,12(26):1-6.
[18] Hingorani N.G. Network access and the future of power transmission [J]. EPRI Journal, April-May,1986:45-52.
[19]李家坤.柔性交流输电技术在电力系统中的应用[J].电力学报,2007,22(3):328-330.
[20]何大愚.柔性交流输电技术和用户电力技术的新进展[J].电力系统自动化,1999,23(6):8-13.
[21]朱海峰,程浩忠,张焰,等.电网灵活规划的研究进展[J].电力系统自动化,1999,23(17):38-41.
[22]程浩忠,阙讯,马则良,等.考虑出力调整和柔性约束的电网规划方法[J].上海交通大学学报,2005,39(3):417-420.
[23]程浩忠,张焰,严正,等.电力系统规划[M].北京:中国电力出版社,2008.
[24] Halemane K.P., Grossmann I.E.. Optimal process design under uncertainty [J]. AIChE Journal,1983,29(3):425-433.
[25] Swaney R.E., Grossmann I.E.. An index for operational flexibility in chemical process design, PartI: Formulation and theory [J]. AIChE Journal,1985,31(4):621-630.
[26]尹清华,江山,陈清林,等.过程系统的柔性分析和弹性设计研究进展与展望[J].炼油设计,2001,31(6):1-7.
[27] Swaney R.E., Grossmann I.E. An index for operational flexibility in chemical process design, PartII: Computational algorithms [J]. AIChE Journal,1985,31(4):631-641.
[28] Shimizu Y. A plain approach for dealing with flexibility problems in linear systems [J]. Computers&Chemical Engineering,1989,13(10):1189-1191.
[29] Varvarezos D.K., Grossmann I.E., Bieglar L.T. A sensitivity based approach for flexibility analysisand design of linear process systems [J]. Computer&Chemical Engineering,1995,19(12):1301-1316.
[30] Kazemi A., Badrzadeh B. Modeling and simulation of SVC and TCSC to study their limits onmaximum loadability point [J]. International Journal of Electrical Power&Energy Systems,2004,26(8):619-626.
[31]彭辉,樊庆玲,刘会金.配电网中TCSC和SVC的联合补偿[J].电力系统及其自动化学报,2002,14(4):16-18.
[32]王树文,纪延超,马文川.灵活交流输电技术[J].电力系统及其自动化学报,2007,19(3):113-117.
[33]李岩松,郭家骥,刘君.应用UPFC控制电力网络潮流的研究[J].电力系统及其自动化学报,2000,12(4):4-8.
[34] Hingorani N.G. FACTS and potential state-of-the-art: opportunities and limitations [C]. ICPST’94,1994, Oct. Beijing.
[35]徐瑞卿.基于盲数的市场环境下电网规划[D].北京交通大学,2007.
[36]金华征,程浩忠.电力市场下的电网灵活规划方法综述[J].电力系统及其自动化学报,2006,18(2):10-17.
[37] Van Geert E. Increased uncertainty a new challenge for power system planners [C]. IEEColloquium on Tools and Techniques for Dealing with Uncertainty, London, UK,1998:1/1-1/6.
[38]程浩忠,朱海峰,马则良,等.基于等微增率准则的电网灵活规划方法[J].上海交通大学学报,2003,37(9):1351-1353.
[39]朱海峰,程浩忠,张焰,等.考虑线路被选概率的电网灵活规划方法[J].电力系统自动化,2000,24(17):20-24.
[40]翟海保,程浩忠,陈春霖,等.基于最小期望悔值的电网灵活规划方法[J].上海交通大学学报,2005,39(9):27-30.
[41]高赐威,程浩忠,王旭.考虑场景发生概率的柔性约束电网规划模型[J].中国电机工程学报,2004,24(11):34-38.
[42] Gorenstin B.G., Campodonico N.M., Costa J.P., et al. Power system expansion planning underuncertainty [J]. IEEE Transactions on Power Systems,1993,8(1):129-136.
[43]张洪明,廖培鸿.输电网规划的灰色模型及算法[J].上海交通大学学报,1995,29(3):20-26.
[44]孙洪波.电力网络规划[M].重庆:重庆大学出版社,1996.
[45]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[J].上海交通大学学报,2003,37(9):1347-1350.
[46]高赐威,程浩忠,王旭.盲信息的模糊评价模型在电网规划中的应用[J].中国电机工程学报,2004,24(9):24-29.
[47]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[J].中国电机工程学报,2006,26(3):7-12.
[48]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[J].中国电机工程学报,2006,26(12):16-20.
[49] Binato S., Pereira M.V.F., Granville S. A new benders decomposition approach to solve powertransmission network design problems [J]. IEEE Transactions on Power Systems,2001,16(2):235-240.
[50] Bahiense L., Dliveira G.C., Pereira M., et al. A mixed integer disjunctive model for transmissionnetwork expansion [J]. IEEE Transactions on Power Systems,2001,16(3):560-565.
[51] Lee K.Y., Manuspiya S., Myeonsong Choi, et al. Network congestion assessment for short-termtransmission planning under deregulated environment [C]. Proceedings of2001IEEE PowerEngineering Society Transmission and Distribution Conference. Columbus, USA,2001,3:1266-1271.
[52] Kandi M.S., EI-Debeiky S.M., Hasanien N.E. A hybrid mathematical and rule-based system fortransmission network planning in a deregulated environment [C]. Proceedings of the IEEE PowerEngineering Society Summer Meeting. Vancouver, Canada,2001,1451-1456.
[53] Kit Po Wong, Yin Wa Wong. Combined genetic algorithm/simulated annealing/fuzzy set approachto short-term generation scheduling with take-or-pay fuel contract [J]. IEEE Transactions onPower Systems,1996,11(1):128-136.
[54] Da Silva E.L., Ortiz J.M.A., De Olivira G.C., et al. Transmission network expansion planningunder a Tabu search approach [J]. IEEE Transactions on Power Systems,2001,16(1):62-68.
[55]翟海保,程浩忠,吕干云,等.多阶段输电网络最优规划的并行蚁群算法[J].电力系统自动化,2004,28(20):37-42.
[56]胡家声,郭创新,叶彬,等.离散粒子群优化算法在输电网络扩展规划中的应用[J].电力系统自动化,2004,28(20):31-36.
[57] Galiana F.D., McGillis D.T., Marin M.A. Expert systems in transmission planning [J]. Proceedingsof the IEEE,1992,80(5):712-726.
[58]韩英铎,严干贵,姜齐荣,等.信息电力与FACTS及DFACTS技术[J].电力系统自动化,2000,24(19):1-7.
[59]韩民晓,肖湘宁,徐永海.柔性化供电技术[J].电力系统自动化,2002,26(8):1-5.
[60] Seki Tomomichi, Seki Toshibumi, Tanaka T, et a1. Flexible network integrated supervisorycontrol for power systems based on distributed objects [J]. Electrical Engineering in Japan,2001,136(4):34-46.
[61]杨海晶,张东英,吴琼,等.电力系统柔性SCADA框架设计及功能分析[J].电网技术,2006,30(15):36-39.
[62]杨海晶,杨以涵,马骞,等.基于IP技术的电力系统柔性SCADA研究与应用[J].继电器,2006,34(21):49-53.
[63]柳焯.最优化原理及其在电力系统中的应用[M].哈尔滨:哈尔滨工业大学出版社,1988.
[64]李彩华,郭志忠.最优潮流的发展[J].继电器,2002,30(1):1-6.
[65]张小平.电力系统潮流和最优潮流分析技术的进展专题简介[J].电力系统自动化,2005,29(16):1.
[66]孙伟卿,王承民,张焰,等.采用柔性化方法表示刚性约束的电力系统柔性优化模型[J].电网技术,2012,36(3):120-126.
[67] Browne J., Dubois D., Rathmill K., et al. Types of flexibility and classification of flexiblemanufacturing systems [J]. The FMS Magazine,1984,2(2):114-117.
[68] Sethi S.K., Sethi S.P. Flexibility in manufacturing: a survey [J]. International Journal of FlexibleManufacturing systems,1990,2:289-328.
[69]孙伟卿,王承民,张焰.智能化电网中的柔性评价方法与应用[J].电网与清洁能源,2011,27(5):5-11.
[70] Zadeh L.A. Fuzzy sets [J]. Information and Control,1965,8:338-353.
[71] Ma R., Yan H.W., Tong X.J. Multiobjective fuzzy optimal transaction planning based optimalpower flow for electricity market [C]. Proceedings of the7th International Power EngineeringConference, November29-December2,2005, Singapore:1-5.
[72] Ramesh V.C., Li X. A fuzzy multiobjective approach to contingency constrained OPF [J]. IEEETransactions on Power Systems,1997,12(3):1348-1354.
[73] Jaeseok C., El-Keib A.A., Tran T. A fuzzy branch and bound-based transmission system expansionplanning for the highest satisfaction level of the decision maker [J]. IEEE Transactions on PowerSystems,2005,20(1):476-484.
[74] Borkowska B. Probabilistic load flow [J]. IEEE Transactions on Power Apparatus and Systems,1974,93(3):752-759.
[75] Leite da Silva A.M., Ribeiro S.M.P., Arienti V.L., et al. Probabilistic load flow techniques appliedto power system expansion planning [J]. IEEE Transactions on Power Systems,1990,5(4):1047-1053.
[76]李雪,李渝曾,李海英.几种概率潮流算法的比较与分析[J].电力系统及其自动化学报,2009,21(3):12-17.
[77] Deng J.L. Control problems of Grey Systems [J]. Systems&Control Letters,1982,1(5):288-294.
[78]吴艳蕾.基于灰理论的居民生活电力消费预测研究[J].安徽工程科技学院学报,2008,23(1):32-34.
[79]姚力文,白小明,陈轶.基于灰理论的电力负荷预测模型[J].南昌大学学报（理科版）,2010,34(5):507-510.
[80] Kundur P., Paserba J., Ajjarapu V., et al. Definition and classification of power system stabilityIEEE/CIGRE joint task force on stability terms and definitions [J]. IEEE Transactions on PowerSystems,2004,19(3):1387-1401.
[81]“Demand-Side Management: The System Operator’s Perspective”, North American ElectricReliability Council (NERC), Princeton, NJ,1993.
[82]李来福,柳焯.需求侧管理在缓解紧急态势中的作用[J].电网技术,2008,32(7):56-60.
[83]张峰.电力负荷管理技术[M].北京:中国电力出版社,2005.
[84] Faranda R., Pievatolo A., Tironi E. Load shedding: a new proposal [J]. IEEE Transaction onPower Systems,2007,22(4):2086-2093.
[85] Concordia C., Fink L.H., Poullikkas G. Load shedding on an isolated system [J]. IEEETransactions on Power Systems,1995,10(3):1467-1472.
[86] Delfino B., Massucco S., Morini A., et al. Implementation and comparison of different underfrequency load-shedding schemes [C]. IEEE Summer Meeting2001, Vancouver, BC, Canada, Jul.15-19,2001,1:307-312.
[87] Ding X., Girgis A.A. Optimal load shedding strategy in power systems with distributed generation[C]. IEEE Power Engineering Society Winter Meeting, Columbus, OH, Feb.2001,2:788-793.
[88]申景双,蒋传文,侯志俭.发电机组超铭牌出力时经济补偿的研究[J].华东电力,2002,30(10):9-10.
[89]中国国家标准化管理委员会. GB/T12325-2008电能质量供电电压偏差[S].北京：中国标准出版社,2008.
[90]叶鸿声,龚大卫,黄伟中.提高导线允许温度增加线路输送容量的研究及在500kV线路上的应用[J].华东电力,2006,34(8):43-46.
[91]陈芳,韩学山,康凯,等.基于SCADA信息追踪输电线路动态热定值[J].电力系统自动化,2010,34(5):81-85.
[92]程浩忠,范宏,翟海保.输电网柔性规划研究综述[J].电力系统及其自动化学报,2007,19(1):21-27.
[93] Cruz-Rodriguez R.D., Latorre-Bayona G. HIPER: interactive tool for mid-term transmissionexpansion planning in a deregulated environment [J]. IEEE Power Engineering Review,2000,20(21):61-62.
[94]袁越,吴博文,李振杰,等.基于多场景概率的含大型风电场的输电网柔性规划[J].电力自动化设备,2009,29(10):8-12.
[95]曾鸣,吕春泉,邱柳青,等.风电并网时基于需求侧响应的输电规划模型[J].电网技术,2011,35(4):129-134.
[96]周金辉,余贻鑫,曾沅.大规模风电接入下输电网扩展规划的启发式优化算法[J].电力系统自动化,2011,35(22):66-70.
[97] Zhao J.H., Foster J., Dong Z.Y., et al. Flexible transmission network planning consideringdistributed generation impacts [J]. IEEE Transactions on Power Systems,2011,26(3):1434-1443.
[98]郑静,文福拴,李力,等.计及风险控制策略的含风电机组的输电系统规划[J].电力系统自动化,2011,35(22):71-76.
[99]白玉东,王承民,衣涛,等.基于柔性分析的风电并网容量优化建模[J].电力系统自动化,2012,36(12):17-24.
[100]白玉东,王承民,衣涛,等.电力系统的柔性评价与风电穿透功率极限计算[J].电力自动化设备,2012,32(10):12-16.
[101]黄德才,赵克勤.用联系数描述和处理网络计划中的不确定性[J].系统工程学报,1999,14(2):112-117.
[102]武鹏.考虑不确定因素的输电网灵活规划方法研究[D].上海交通大学,2009.
[103]于群,曹娜,郭剑波.负载率对电力系统自组织临界状态的影响分析[J].电力系统自动化,2012,36(1):24-27.
[104]常康,韩学山,王孟夏,等.电网关键元件及其单调性研究I：概念与基础[J].电力系统保护与控制,2009,37(6):1-5.
[105]梁才,刘文颖,温志伟,等.电网组织结构对其自组织临界性的影响[J].电力系统保护与控制,2010,38(20):6-11.
[106]赵书强,王磊.改进蚁群算法在配电网规划中的应用电力系统保护与控制[J].电力系统保护与控制,2010,38(24):61-65.
[107]Romero R., Monticelli A., Garcia A., et al. Test systems and mathematical models fortransmission network expansion planning [J]．IEE Proceedings–Generation, Transmission&Distribution,2002,149(1):27-36.
[108]Li F.X., Qiao W., Sun H.B., et al. Smart transmission grid: vision and framework [J]. IEEETransactions on Smart Grid,2010,1(2):168-177.
[109]Jabr R.A, Coonick A.H., Cory B.J. A homogeneous linear programming algorithm for the securityconstrained economic dispatch problem [J]. IEEE Transactions on Power Systems,2000,15(3):930-936.
[110]Henke R.K., Sciacca S.C. Dynamic thermal rating of critical lines-a study of real-time interfacerequirements [J]. IEEE Computer Applications in Power,1989,2(3):46-51.
[111]Foss S.D., Maraio R.A. Dynamic line rating in the operating environment [J]. IEEE Transactionson Power Delivery,1990,5(2):1095-1105.
[112]Seppa T.O. Increasing transmission capacity by real time monitoring [J]. IEEE Power EngineeringSociety Winter Meeting,2002,2:1208-1211.
[113]Wiszniewski A. New criteria of voltage instability margin for the purpose of load shedding [J].IEEE Transactions on Power Delivery,2007,22(3):1367-1371.
[114]Wan H., McCalley J.D., Vittal, V. Increasing thermal rating by risk analysis [J]. IEEETransactions on Power Systems,1999,14(3):815-828.
[115]Musilek P., Heckenbergerova J., Bhuiyan M.M.I. Spatial analysis of thermal aging of overheadtransmission conductors [J]. IEEE Transactions on Power Delivery,2012,27(3):1196-1204.
[116]Kim D.M., Kim J.O. Prediction of transmission-line rating based on thermal overload probabilityusing weather models [J]. European Transactions on Electrical Power,2010,20(4):534-544.
[117]Hosek J., Musilek P., Lozowski E., et al. Effect of time resolution of meteorological inputs ondynamic thermal rating calculations [J]. IET Generation, Transmission&Distribution,2011,5(9):941-947.
[118]Saied M.M. Assessing the dynamic rating of overhead transmission lines [J]. EuropeanTransactions on Electrical Power,2007,17(5):526-536.
[119]Heckenbergerova J., Musilek P., Filimonenkov K. Quantification of gains and risks of staticthermal rating based on typical meteorological year [J]. International Journal of Electrical Power&Energy Systems,2013,44(1):227-235.
[120]王益民.坚强智能电网技术标准体系研究框架[J].电力系统自动化,2010,34(22):1-6.
[121]Hur K., Boddeti M., Sarma N.D.R., et al. High-wire act [J]. IEEE Power and Energy Magazine,2010,8(1):37-45.
[122]Albizu I., Fernandez E., Mazon A.J., et al. Influence of the conductor temperature error on theoverhead line ampacity monitoring systems [J]. IET Generation, Transmission&Distribution,2011,5(4):440-447.
[123]Siwy E. Risk analysis in dynamic thermal overhead line rating [C]. International Conference onProbabilistic Methods Applied to Power Systems, Stockholm, Sweden, June2006:1-5.
[124]Chu R.F. On selecting transmission lines for dynamic thermal line rating system implementation[J]. IEEE Transactions on Power Systems,1992,7(2):612-619.
[125]Ahmed M.A.H., Azah M., Aini H. Vulnerability control of large scale interconnected powersystem using neuro-fuzzy load shedding approach [J]. Expert System with Applications,2010,37(4):3171-3176.
[126]Wang Y., Pordanjani I.R., Li W., et al. Strategy to minimise the load shedding amount for voltagecollapse prevention [J]. IET Generation, Transmission&Distribution,2011,5(3):307-313.
[127]Ghaleh A.P., Sanaye-Pasand M., Saffarian A. Power system stability enhancement using a newcombinational load-shedding algorithm [J] IET Generation, Transmission&Distribution,2011,5(5):551-560.
[128]Varadarajan M., Swarup K.S. Solving multi-objective optimal power flow using differentialevolution [J]. IET Generation, Transmission&Distribution,2008,2(5):720-730.
[129]Sun D.I., Ashley B., Brewer B., et al. Optimal power flow by Newton approach [J]. IEEETransactions on Power Apparatus and Systems,1984,103(10):2864-2880.
[130]滕乐天.电动汽车充电机（站）设计[M].北京:中国电力出版社,2009.
[131]高赐威,张亮.电动汽车充电对电网影响的综述[J].电网技术,2011,35(2):127-131.
[132]徐立中,杨光亚,许昭,等.电动汽车充电负荷对丹麦配电系统的影响[J].电力系统自动化,2011,35(14):18-23.
[133]Fernández L.P., Román T.G.S., Cossent R., et al. Assessment of the Impact of Plug-in ElectricVehicles on Distribution Networks [J]. IEEE Transactions on Power Systems,2011,26(1):206-213.
[134]鲍冠南,陆超,袁志昌,等.基于动态规划的电池储能系统削峰填谷实时优化[J].电力系统自动化,2012,36(12):11-16.
[135]赵俊华,文福拴,杨爱民,等.电动汽车对电力系统的影响及其调度与控制问题[J].电力系统自动化,2011,35(14):2-10.
[136]胡泽春,宋永华,徐智威,等.电动汽车接入电网的影响与利用[J].中国电机工程学报,2012,32(4):1-10.
[137]徐智威,胡泽春,宋永华,等.充电站内电动汽车有序充电策略[J].电力系统自动化,2012,36(11):38-43.
[138]姚伟锋,赵俊华,文福拴,等.基于双层优化的电动汽车充放电调度策略[J].电力系统自动化,2012,36(11):30-37.
[139]张舒,胡泽春,宋永华,等.考虑电动汽车换电站与电网互动的机组组合问题研究[J].中国电机工程学报,2012,32(10):49-55.
[140]Clement K, Haesen E, Driesen J. The impact of charging plug-in hybrid electric vehicles on aresidential distribution grid [J]. IEEE Transactions on Power Systems,2010,25(1):371-380.
[141]王丹,龙亮,葛琪,等.基于低谷填入法的插电式混合动力汽车集中充电策略[J].电力需求侧管理,2010,12(6):8-11.
[142]康继光,卫振林,程丹明,等.电动汽车充电模式与充电站建设研究[J].电力需求侧管理,2009(5):64-66.
[143]岳思,李艳.电动汽车充电模式及方式浅析[J].通信电源技术,2012,29(2):38-40.
[144]刘晓飞,张千帆,崔淑梅.电动汽车V2G技术综述[J].电工技术学报,2012,27(2):121-127.
[145]Ota Y., Taniguchi H., Nakajima T., et al. An autonomous distributed vehicle-to-grid control ofgrid-connected electric vehicle [C]. Industrial and Information Systems (ICIIS),2009:414-418.
[146]Saber A.Y., Venayagamoorthy G.K. Unit commitment with vehicle-to-grid using particle swarmoptimization [C]. IEEE Bucharest Power Tech,2009:1-8.
[147]薛飞,雷宪章,张野飚,等.电动汽车与智能电网从V2G到B2G的全新结合模式[J].电网技术,2012,36(2):29-34.
[148]薛晨,黎灿兵,曹一家,等.智能电网中的电网友好技术概述及展望[J].电力系统自动化,2011,35(15):102-107.
[149]王蓓蓓,李扬,高赐威.智能电网框架下的需求侧管理展望与思考[J].电力系统自动化,2009,33(20):17-22.
[150]Moghaddam M.P., Baboli P.T., Alishahi E, et al. Flexible load following the wind powergeneration [C]. IEEE International Energy Conference and Exhibition (EnergyCon),2010:802-807.
[151]孙伟卿,王承民,张焰.智能电网中的柔性负荷[J].电力需求侧管理,2012,14(3):10-13.
[152]曹一家,谭益,黎灿兵,等.具有反向放电能力的电动汽车充电设施入网典型方案[J].电力系统自动化,2011,35(14):48-52.
[153]徐丙垠,李天友,薛永端.智能配电网与配电自动化[J].电力系统自动化,2009,33(17):38-41.
[154]李燕.负荷的削峰填谷与电网的经济运行[J].电工电气,2011,5:42-44.
[155]殷树刚,苗文静,拜克明.准实时电价策略探析[J].电力需求侧管理,2011,13(1):20-23.
[156]罗卓伟,胡泽春,宋永华,等.大规模电动汽车充放电优化控制及容量效益分析[J].电力系统自动化,2012,36(10):19-26.
[157]段登伟,刘俊勇,吴集光.计及风险的配电公司最优分时零售电价模型[J].电力系统自动化,2005,29(3):8-12.
[158]Zhang W.J., Li F.X., Tolbert L.M. Review of reactive power planning: objectives, constraints, andalgorithms [J]. IEEE Transactions on Power Systems,2007,22(4):2177-2186.
[159]孙伟卿,王承民,张焰,等.基于Pareto最优的电力系统有功－无功综合优化[J].电力系统自动化,2009,33(10):38-42.
[160]郑晓,张静,马韬韬,等.基于改进决策方法的电力系统多目标优化调度[J].电工技术学报,2010,25(9):151-156.
[161]韩学山,赵建国.刚性优化与柔性决策结合的电力系统运行调度理论探讨[J].中国电力,2004,37(1):15-18.
[162]张强,韩学山,徐建政.安全经济调度与均匀调度间关系分析[J].电力系统及其自动化学报,2005,17(2):84-89.
[163]常康,韩学山,王孟夏,等.电网关键元件及其单调性研究I：概念与基础[J].电力系统保护与控制,2009,37(6):1-5.
[164]梁才,刘文颖,温志伟,等.电网组织结构对其自组织临界性的影响[J].电力系统保护与控制,2010,38(20):6-11.
[165]史进,涂光瑜,罗毅.电力系统复杂网络特性分析与模型改进[J].中国电机工程学报,2008,28(25):93-98.
[166]徐林,王秀丽,王锡凡.使用等值导纳进行电力系统小世界特性识别[J].中国电机工程学报,2009,29(19):20-26.
[167]赵鸿图,朱治中,于尔铿.电力市场中需求响应市场与需求响应项目研究[J].电网技术,2010,34(5):146-153.
[168]曾鸣,张艳馥,王鹤,等.基于综合资源规划的供需资源优化组合模型[J].电力系统自动化,2007,31(3):24-28.
[169]王蓓蓓,李扬.面向智能电网的电力需求侧管理规划及实施机制[J].电力自动化设备,2010,30(12):19-24.
[170]Wang H., Murillo-Sanchez C.E., Zimmerman R.D., et al. On computational issues ofmarket-based optimal power flow [J]. IEEE Transactions on Power Systems,2007,22(3):1185-1193.