电力系统恢复控制的协调优化策略研究
|
摘要
现代电力系统随着市场机制的引入而日趋复杂。日益增长的负荷需求与设备的相对老化之间的矛盾导致系统接近其运行稳定极限,易在级联故障条件下引发大停电事故。因此,如何在事故发生后快速、高效地恢复系统运行是电力系统研究领域的重要课题。本文在学习和借鉴已有研究工作的基础上,提出一套全新的现代电力系统恢复控制的优化体系,着重从模型建立、求解策略、协作优化、整体寻优、时步概念、以及交互策略等方面进行研究。提高恢复控制的智能水平,改善总体优化效果,促成由传统的经验性决策方式向规范化、标准化决策方式的转变。论文工作包括以下几方面:
(1)按照优化对象的不同,将恢复控制划分为机组启动的优化、网络重构的优化和负荷恢复的优化,研究各自的优化目标和约束条件。提出电力系统恢复控制协调优化策略的总体框架,为恢复控制的优化提供一种新的思路。
(2)提出机组启动的优化模型和求解策略。模型以优化时间段内机组发电量最大为全局优化目标,同时计及各种约束条件。通过采用基于数据包络分析模型的相对有效性评估的定性方法与利用回溯算法求解背包问题的定量方法相结合的方式进行求解。所提方法能较好地权衡对所求解问题的快速性和正确性要求。
(3)提出最优送电路径的通用模型和相应的智能优化算法解算模式。以寻找最短加权送电路径为优化目标,将网络重构建模为一个寻找图的Steiner树问题。利用遗传算法进行求解,并对算法本身进行优化以提高求解速度、稳定性和寻优效率。
(4)将传统意义的负荷恢复扩展到网络框架还未完全恢复的阶段,提出该阶段负荷重要性评价模型和负荷恢复优化模型,以及相应的求解策略。优化模型在数学上构成一个多属性决策问题,利用基于偏好数据包络分析(DEA)的评价方法对负荷进行相对重要性评估,采用基于价值密度的贪心算法确定优先恢复的负荷点。
(5)研究机组启动、网络重构和负荷恢复之间的协作机制。以恢复控制优化策略的总体框架为基础,提出一种基于短期目标网的交互式恢复控制策略。利用离散化技术,将恢复控制这一整体问题分解为每一时步的子问题。在恢复过程的每一时步,以前一时步已经恢复的系统为基础,通过整体寻优,确定当前时步优先恢复的机组、线路和负荷点,由此构成综合指标最优或次最优的若干目标网络,逐步引导恢复控制过程。采用交互式技术,保证决策过程与实际恢复控制过程的结合。提出多智能体恢复控制优化决策体系的设计思想,研究各智能体之间的协作机制,提出恢复控制优化决策体系的协作模型。
Modern power systems have become more and more complex due to the introduction of the deregulated and unbundled power market operational mechanism. Conflict between increased load demand and the aged equipments has also pushed power systems to be operated close to their limits, which is increasing the risk of large blackouts after the cascading failures. Accordingly, how to restore power systems rapidly and effectively after blackouts has become more and more important issue of interest in power engineering. Based on the existing literature survey investigated thoroughly to power system restoration, a novel global intelligent optimization framework towards modern power system restorative control is proposed in this thesis. The key points of this research involve the construction of optimization model, the solution strategy, the behavior of collaborative optimization, the overall optimization target, the concept of time step and the interactive strategy, etc. This research can enhance the restorative control level and improve the whole optimization results, on the other hand, can implement the transformation of decision-making mode of power system restoration control from the traditional experience-driven strategy to the standardization and normalization strategy. The main achievements are as follows:
1. With respect to the specific optimization objective, the whole power system restoration problem can be supposed to be divided into the optimal units start-up, the optimal network reconfiguration, and the optimal load recovery. The corresponding optimization models and the constraint conditions were studied in this thesis. The framework of the optimal strategy for the power system restoration was proposed, which can provide a new way to implement the optimization of the power system restoration.
2. An optimal strategy involving the corresponding model and approach to units start-up were presented. The objective of the model is to maximize the total power generation capability (MWh) over a restoration period whilst being subjected to the specific constraints. The proposed model is a typical multi-constraint knapsack problem from the mathematical point of view. The combination of the data envelopment analysis (DEA) method and by solving the knapsack problem was employed to determine the units to be cranked. The proposed method, to some extent, can make the trade off between the simulation accuracy and the computing efforts better.
3. An optimal strategy involving the corresponding model and approach for the network reconfiguration were presented. The goal of the proposed model is to find the shortest weighted path for units start-up or load recovery in restoration duration whilst considering all kinds of constraints. The proposed model is considered as a typical Steiner tree problem from the mathematical point of view. The genetic algorithm method with characteristics of global optimization and handling the discrete variables easily and effectively was employed to solve this problem. Furthermore, the performance of genetic algorithm was optimized in order to improve calculation speed, stability and search efficiency further.
4. A novel evaluation model for the importance of load and a load recovery optimization model as well as the solution strategy with respect to the period when the network is still reconfiguring, which are different from the traditional concept of the load recovery, were proposed in this thesis. From the mathematical point of view, the proposed model is a multi-attribute decision making problem. The DEA method with preference information and the value of density of pi/wi greedy algorithm were employed to determine the loads to be recovered.
5. The interactive and collaborative mechanism during units start-up, network reconfiguration and load recovery was studied in this thesis. An interative strategy with respect to the restorative control based on the short-term-target-network was presented. The whole restorative control problem was discretized as a series of optimization problem in each time step. In each time step, according to the restored system in last time step, the corresponding optimal target networks with the units, networks and loads to be restored at current time step can be determined based on the global optimization technique. These restored short-term-target-networks can guide the restoration process step by step effectively. Furthermore, the decision making process can be combined with the actual restoration process by the interative techniques. A Multi-Agent System based optimal strategy framework towards restoration control was proposed. The corresponding collaborative mechanism among Agents was studied as well. Finally, the coordination model of the optimal strategy towards restorative control was presented.
(1)按照优化对象的不同,将恢复控制划分为机组启动的优化、网络重构的优化和负荷恢复的优化,研究各自的优化目标和约束条件。提出电力系统恢复控制协调优化策略的总体框架,为恢复控制的优化提供一种新的思路。
(2)提出机组启动的优化模型和求解策略。模型以优化时间段内机组发电量最大为全局优化目标,同时计及各种约束条件。通过采用基于数据包络分析模型的相对有效性评估的定性方法与利用回溯算法求解背包问题的定量方法相结合的方式进行求解。所提方法能较好地权衡对所求解问题的快速性和正确性要求。
(3)提出最优送电路径的通用模型和相应的智能优化算法解算模式。以寻找最短加权送电路径为优化目标,将网络重构建模为一个寻找图的Steiner树问题。利用遗传算法进行求解,并对算法本身进行优化以提高求解速度、稳定性和寻优效率。
(4)将传统意义的负荷恢复扩展到网络框架还未完全恢复的阶段,提出该阶段负荷重要性评价模型和负荷恢复优化模型,以及相应的求解策略。优化模型在数学上构成一个多属性决策问题,利用基于偏好数据包络分析(DEA)的评价方法对负荷进行相对重要性评估,采用基于价值密度的贪心算法确定优先恢复的负荷点。
(5)研究机组启动、网络重构和负荷恢复之间的协作机制。以恢复控制优化策略的总体框架为基础,提出一种基于短期目标网的交互式恢复控制策略。利用离散化技术,将恢复控制这一整体问题分解为每一时步的子问题。在恢复过程的每一时步,以前一时步已经恢复的系统为基础,通过整体寻优,确定当前时步优先恢复的机组、线路和负荷点,由此构成综合指标最优或次最优的若干目标网络,逐步引导恢复控制过程。采用交互式技术,保证决策过程与实际恢复控制过程的结合。提出多智能体恢复控制优化决策体系的设计思想,研究各智能体之间的协作机制,提出恢复控制优化决策体系的协作模型。
Modern power systems have become more and more complex due to the introduction of the deregulated and unbundled power market operational mechanism. Conflict between increased load demand and the aged equipments has also pushed power systems to be operated close to their limits, which is increasing the risk of large blackouts after the cascading failures. Accordingly, how to restore power systems rapidly and effectively after blackouts has become more and more important issue of interest in power engineering. Based on the existing literature survey investigated thoroughly to power system restoration, a novel global intelligent optimization framework towards modern power system restorative control is proposed in this thesis. The key points of this research involve the construction of optimization model, the solution strategy, the behavior of collaborative optimization, the overall optimization target, the concept of time step and the interactive strategy, etc. This research can enhance the restorative control level and improve the whole optimization results, on the other hand, can implement the transformation of decision-making mode of power system restoration control from the traditional experience-driven strategy to the standardization and normalization strategy. The main achievements are as follows:
1. With respect to the specific optimization objective, the whole power system restoration problem can be supposed to be divided into the optimal units start-up, the optimal network reconfiguration, and the optimal load recovery. The corresponding optimization models and the constraint conditions were studied in this thesis. The framework of the optimal strategy for the power system restoration was proposed, which can provide a new way to implement the optimization of the power system restoration.
2. An optimal strategy involving the corresponding model and approach to units start-up were presented. The objective of the model is to maximize the total power generation capability (MWh) over a restoration period whilst being subjected to the specific constraints. The proposed model is a typical multi-constraint knapsack problem from the mathematical point of view. The combination of the data envelopment analysis (DEA) method and by solving the knapsack problem was employed to determine the units to be cranked. The proposed method, to some extent, can make the trade off between the simulation accuracy and the computing efforts better.
3. An optimal strategy involving the corresponding model and approach for the network reconfiguration were presented. The goal of the proposed model is to find the shortest weighted path for units start-up or load recovery in restoration duration whilst considering all kinds of constraints. The proposed model is considered as a typical Steiner tree problem from the mathematical point of view. The genetic algorithm method with characteristics of global optimization and handling the discrete variables easily and effectively was employed to solve this problem. Furthermore, the performance of genetic algorithm was optimized in order to improve calculation speed, stability and search efficiency further.
4. A novel evaluation model for the importance of load and a load recovery optimization model as well as the solution strategy with respect to the period when the network is still reconfiguring, which are different from the traditional concept of the load recovery, were proposed in this thesis. From the mathematical point of view, the proposed model is a multi-attribute decision making problem. The DEA method with preference information and the value of density of pi/wi greedy algorithm were employed to determine the loads to be recovered.
5. The interactive and collaborative mechanism during units start-up, network reconfiguration and load recovery was studied in this thesis. An interative strategy with respect to the restorative control based on the short-term-target-network was presented. The whole restorative control problem was discretized as a series of optimization problem in each time step. In each time step, according to the restored system in last time step, the corresponding optimal target networks with the units, networks and loads to be restored at current time step can be determined based on the global optimization technique. These restored short-term-target-networks can guide the restoration process step by step effectively. Furthermore, the decision making process can be combined with the actual restoration process by the interative techniques. A Multi-Agent System based optimal strategy framework towards restoration control was proposed. The corresponding collaborative mechanism among Agents was studied as well. Finally, the coordination model of the optimal strategy towards restorative control was presented.
引文
[1] US-Canada Power Outage Task Force. Final report on the August 14th 2003 blackout in the United States and Canada [EB/OL]. http://www.ferc.gov
[2] Andersson G,Donalek P,Farmer R,et al. Causes of the 2003 major grid blackouts in North America and Europe,and recommended means to improve system dynamic performance. IEEE Transactions on Power Systems,2005,20(4):1922-1928
[3] Makarov Y V,Reshetov V I,Stroev A,et al. Blackout prevention in the united states,Europe,and Russia. Proceedings of the IEEE,2005,93(11):1942-1955
[4]葛睿,董昱,吕跃春.欧洲11. 4大停电事故分析及对我国电网运行工作的启示.电网技术,2007,31(3):1-6
[5]陈向宜,陈允平,李春艳,等.构建大电网安全防御体系—欧洲大停电事故的分析及思考.电力系统自动化,2007,31(1):4-8
[6]王梅义,吴竞昌,蒙定中.大电网系统技术(第二版).北京:中国电力出版社,1995. 10-64
[7] Pereira L. Cascade to black [system blackouts]. IEEE Power and Energy Magazine, 2004,2(3):54-57
[8] Horowitz S H,Phadke A G. Boosting immunity to blackouts. Power and Energy Magazine,2003,1(5):47-53
[9] Roger Kearsley. Restoration in Sweden and experience gained from the blackout of 1983. IEEE Transactions on Power Systems,1987,2(2):422-428
[10] Salvati R,Sforna M,Pozzi M. Restoration project [Italian power restoration plan]. IEEE Power and Energy Magazine,2004,2(1):44-51
[11]唐斯庆,张弥,李建设,等.海南电网“9.26”大面积停电事故的分析与总结.电力系统自动化,2006,30(1):1-7,16
[12]何大愚.一年以后对美加“8.14”大停电事故的反思.电网技术,2004,28(21):1-5
[13] Adibi M M,Clelland P,Fink L,et al. Power system restoration - a task force report. IEEE Transactions on Power Systems,1987,2(2):271-277
[14] Adibi M M,Borkoski J N,Kafka R J. Power system restoration - the second task force report. IEEE Transactions on Power Systems,1987,2(4):927-933
[15] Wu F F,Monicelli A. Analytical tools for power system restoration - conceptual design. IEEE Transactions on Power Systems,1988,3(1):10-16
[16]房鑫炎,郁惟镛,熊惠敏,等.电力系统黑启动的研究.中国电力,2000,33(1):40-43,96
[17]刘隽,李兴源,许秀芳.互联电网的黑启动策略及相关问题.电力系统自动化,2004,28(5):93-97
[18] Adibi M M,Kafka R J. Power system restoration issues. IEEE Computer Application in Power,1991,4(2):19-24
[19] Adibi M M,Fink L H,Andrews C J,et al. Special considerations in power system restoration. IEEE Transactions on Power Systems,1992,7(4):1419-1424
[20] Adibi M M,Fink L H. Power system restoration planning. IEEE Transactions on Power Systems,1994,9(1):22-28
[21] Fink L H,Liou K L,Liu C C. From generic restoration actions to specific restoration stragies. IEEE Transactions on Power Systems,1995,10(2):745-751
[22]郭嘉阳,吴涛,张仁伟,等.华北电网“黑启动”试验研究.华北电力技术,2001,(5):3-18
[23]阮前途,王伟,黄玉,等.基于燃机机组的上海电网黑启动系列试验.电网技术,2006,30(2):19-22
[24] Lindenmeyer D,Dommel H W,Kundur P,et al. A framework for black start and power system restoration. Proceedings of the 2000 IEEE Canadian Conference on Electrical and Computer Engineering,Halifax,Nova Scotia,Canada,May. 2000:153-157
[25]刘艳,顾雪平,张丹.基于数据包络分析模型的电力系统黑启动方案相对有效性评估.中国电机工程学报, 2006,26(5):32-37,94
[26] Islam S,Chowdhury N. A case-based expert system for power system restoration. Proceedings of the 1999 IEEE Canadian Conference on Electrical and Computer Engineering,Edmonton,AB,Canada,May. 1999,2:1159-1163
[27] Germano Lambert-Torres,Luiz Eduardo Borges da Silva,Guilherme Moutinho Ribeiro,et al. An intelligent tool for power system restoration:an example using CESP. International Conference on Power System Technology,Kunming,China,Oct. 2000,2:1131-1136
[28] Chen Chao-Shun,Lin Chai-Hung,Tsai Hung-Ying. A rule based expert system with colored Petri net models for distribution system service restoration. IEEE Transactions on Power Systems,2002,17(4):1073-1080
[29] Salek K,Spanel U,Krost G. Flexible support for operators in restoring bulk power systems. CIGRE/IEEE PES International Symposium on Quality and Security of Electric Power Delivery Systems,Montreal,Canada,Oct. 2003:187-192
[30]王洪涛,刘玉田,丘夕照.基于分层案例推理的黑启动决策支持系统.电力系统自动化,2004,28(11):49-52
[31] Chin Hong-Chan,Su Yuh-Sheng. Application of the Ant-Based network for power system restoration. IEEE/PES Transmission and Distribution Conference and Exhibition:Asia and Pacific,Dalian,China,Aug. 2005:1-5
[32] Nagata T,Tao Y,Fujita H. An autonomous agent for power system restoration. IEEE Power Engineering Society General Meeting,Denver,CO,USA,June. 2004,1:1069-1074
[33] Solanki J M,Schulz N N,Gao Wenzhong. Reconfiguration for restoration of power systems using a multi-agent system. Power Symposium Proceedings of the 37th Annual North American,Ames,Iowa,USA,Oct. 2005:390-395
[34] Liu Dong,Chen Yunping,Shen Guang,et al. A multi-agent based approach for modeling and simulation of bulk power system restoration. IEEE/PES Transmission and Distribution Conference and Exhibition:Asia and Pacific,Dalian,China,Aug. 2005:1-6
[35] Nagata T,Tahara Y,Fujita H. An agent approach to bulk power system restoration. IEEE Power Engineering Society General Meeting,San Francisco,California,USA,Jun. 2005:1312-1317
[36] Li Ling,Liao Zhiwei,Huang Shaoxian,et al. A distributed model for power system restoration based on Ant Colony optimization algorithm. IEEE/PES Transmission and Distribution Conference and Exhibition:Asia and Pacific,Dalian,China,Aug. 2005:15-18
[37] Cooper M E,Adibi M M. Bulk power system restoration training teniques. IEEE Transactions on Power Systems,1993,8(1):191-197
[38] Miller G,Storey A,Vadari V,et al. Experiences using the dispatcher training simulator as a training tool. IEEE Transactions on Power Systems,1993,8(3):1126-1132
[39] Islam S,Chowdhury N. A case-based Windows graphic package for the education and training of power system restoration. IEEE Transactions on Power Systems,2001,16(2):181-187
[40] Sforna M,Bertanza V C. Restoration testing and training in Italian ISO. IEEE Transactions on Power Systems,2002,17(4):1258-1264
[41] Silva A,Vale Z,Ramos C. Cooperative training of power systems restoration techniques. Proceedings of the 13th International Conference on Intelligent Systems Application to Power Systems,Seoul,Korea,Nov. 2005:36-42
[42]张慎明,姚建国.调度员培训仿真系统(DTS)的现状和发展趋势.电网技术,2002,26(7):60-66
[43]孙宏斌,吴文传,张伯明.电网调度员培训仿真系统的新特性和概念扩展.电力系统自动化,2005,29(7):6-11
[44] Adibi M M,Borkoski J N,Kafka R J,et al. Frequency response of prime movers during restoration. IEEE Transactions on Power Systems,1999,14(2):751-756
[45] Jadid S,Salami A. Accurate model of hydroelectric power plant for load pickup during power system restoration. IEEE TENCON 2004,Chiang Mai,Thailand,Nov. 2004 (3):307-310
[46] Furukawa K,Izena A,Shimojo T,et al. Governor control study at the time of a black start. IEEE Power Engineering Society General Meeting,Denver,CO,USA,June. 2004 (2):1521-1526
[47] Nadira R,Dy Liacco T E,Loparo K A. A hierarchical interactive approach to electric power system restoration. IEEE Transactions on Power Systems,1992,7(3):1123-1131
[48]周云海,闵勇.恢复控制中的系统重构优化算法研究.中国电机工程学报,2003,23(4):67-70,188
[49] Ihara S,Schweppe F C. Physically based modeling of cold load pickup. IEEE Transactions on Power Apparatus and Systems,1981,100(9):4142-4150
[50] Chavali S,Pahwa A,Das S. A genetic algorithm approach for optimal distribution feeder restoration during cold load pickup. Proceeding of the 2002 Congress on Evolutionary Computation,Honolulu,Hawaii,USA,May. 2002:1816-1819
[51] Mohanty I. Ant algorithms for the optimal restoration of distribution feeders during cold load pickup. IEEE swarm Intelligence Symposium,Indianapolis,Indiana,USA,April. 2003:132-137
[52]周云海,闵勇.负荷的快速恢复算法研究.中国电机工程学报,2003,23(3):74-79
[53] Wang Qin,Ajjarapu V. A novel approach to implement generic load restoration in continuation-based quasi-steady-state analysis. IEEE Transactions on Power Systems,2005,20(1):516-518
[54] Huang S J,Huang C C. Adaptive approach to load shedding including pumped-storage units during underfrequency conditions. IEE Proceedings - Generation,Transmission and Distribution,2001,148(2):165-171
[55] Quaia S,Marchesin A,Marsigli B,et al. Using pumped storage loads in restoration paths:a field test in the Italian national grid. IEEE Transactions on Power Systems,2005,20(2):1580-1587
[56] Adibi M M,Alexander R W,Avramovic B. Overvoltage control during restoration. IEEE Transactions on Power Systems,1992,7(4):1464-1470
[57] Adibi M M,Milanicz D P. Reactive capability limitation of synchronous machines. IEEE Transactions on Power Systems,1994,9(1):29-40
[58] Adibi M M,Milanicz D P,Volkmann T L. Optimizing generator reactive power resources. IEEE Transactions on Power Systems,1999,14(1):319-324
[59] Adibi M M,Polyak R A,Griva I A,et al. Optimal transformer tap selection using modified barrier-augmented Lagrangian method. IEEE Transactions on Power Systems,2003,18(1):251-257
[60] Adibi M M,Alexander R W,Milanicz D P. Energizing high and extra-high voltage lines during restoration. IEEE Transactions on Power Systems,1999,14(3):1121-1126
[61]程改红,徐政.电力系统故障恢复过程中的过电压控制.电网技术,2004,28(11):29-33
[62]钱家骊,袁大陆,徐国政.对1000kV电网操作过电压及相位控制高压断路器的讨论.电网技术,2005,29(10):1-4,8
[63]张玉琼,顾雪平.基于随机统计分析的黑启动操作过电压的计算校验.电工技术学报,2005,20(5):92-97
[64]李膨源,顾雪平.基于神经网络的黑启动操作过电压快速预测.电网技术,2006,30(3):66-70
[65] Ketabi A,Ranjbar A M,Feuillet R. Analysis and control of temporary overvoltages for automated restoration planning. IEEE Transactions on Power Systems,2002,17(4):1121-1127
[66]程改红,徐政.电力系统故障恢复初期的谐波过电压问题.电网技术,2005,29(10):14-19
[67] Adibi M M , Milanicz D P. Protective system issues during restoration. IEEE Transactions on Power Systems,1995,10(3):1492-1497
[68] Sidhu T S,Tziouvaras D A,Apostolov A P,et al. Protection issues during system restoration. IEEE Transactions on Power Delivery,2005,20(1):47-56
[69]刘映尚,张碧华,周云海.黑启动过程中继电保护和安全自动装置的特性和运行.中国电力,2005,38(5):25-28
[70] Wunderlich S,Adibi M M,Fischl R,et al. An approach to standing phase angle reduction. IEEE Transactions on Power Systems,1994,9(1):470-478
[71] Hazarika D,Sinha A K. An algorithm for standing phase angle reduction for power system restoration. IEEE Transactions on Power Systems,1999,14(4):1213-1218
[72] Hazarika D,Sinha A K. Standing phase angle reduction for power system restoration. IEE Proceedings - Generation, Transmission and Distribution,1998,145(1):82-88
[73] Martins N,De Oliveira E J,Pereira J L R,et al. Reducing standing phase angles via interior point optimum power flow for improved system restoration [C]. IEEE PES Power Systems Conference and Exposition,New York,USA,Oct. 2004:404-408
[74]李阳坡,顾雪平,刘艳.电力系统黑启动过程中线路继电保护的配置与整定.电力系统自动化,2006,30(7):89-92,107
[75] Lu Ying,Kao Wen-Shiow,Chen Yung-Tien. Study of applying load shedding scheme with dynamic D-factor values of various dynamic load models to Taiwan power system. IEEE Transactions on Power Systems,2005,20(4):1976-1984
[76] Liu C C,Liou K L,Chu R F,et al. Generation capability dispatch for bulk power system restoration:a knowledge-based approach. IEEE Transactions on Power Systems,1993,8(1):316-325
[77]董张卓,焦建林,孙启宏.用层次分析法安排电力系统事故后火电机组恢复的次序.电网技术,1997,21(6):48-51,54
[78] Ketabi A,Asmar H,Ranjabar A M,et al. An approach for optimal units start-up during bulk power system restoration. Large Engineering Systems Conference on Power Engineering,Halifax,Nova Scotia,Canada,July. 2001:190-194
[79]刘艳,顾雪平.基于节点重要度评价的骨架网络重构.中国电机工程学报,2007,27(10):20-27
[80]周云海,刘映尚,胡翔勇.大停电事故后的系统网架恢复.中国电机工程学报,2008,28(10):32-36
[81]张志毅,陈允平,袁荣湘.电力系统负荷恢复问题的混合遗传算法求解.电工技术学报,2007,22(2):105-109
[82] NERC. NERC planning standards. North American Electric Reliability Council,1997
[83]中华人民共和国国家经济贸易委员会. DL/T 723-2000.电力系统安全稳定控制技术导则.北京:中国电力出版社,2001
[84]周云海,胡翔勇.恢复控制的一般策略和实例分析.三峡大学学报(自然科学版),2003,25(5):426-428
[85]张文亮,周孝信,白晓民,等.城市电网应对突发事件保障供电安全的对策研究.中国电机工程学报,2008,28(22):1-7
[86]胡键,郭志忠,刘迎春,等.故障恢复问题和发电机恢复排序分析.电网技术,2004,28(18):1-4,15
[87] Adibi M M,Martins N. Power system restoration dynamics issues. IEEE Power Energy Society General Meeting,Pittesburgh,Pennsylvania,USA,July. 2008:1-8
[88] De Mello F P,Westcott J C. Steam plant startup and control in system restoration. IEEE Transactions on Power Systems,1994,9(1):93-101
[89]钱颂迪,胡运权.运筹学.北京:清华大学出版社,1997. 236-239
[90]魏权龄.数据包络分析.北京:科学出版社,2004. 1-58
[91] Charnes A,Cooper W W,Rhodes E. Measuring the efficiency of decision making units. European Journal of Operations Research,1978,2(6):429-444
[92] Lewin A Y,Morey R C. Measuring the relative efficiency and output potential of public sector organizations:an application of data envelopment analysis. International Journal of Policy Analysis and Information Systems,1981,5(4):267-285
[93] Chitkara P,A data envelopment analysis approach to evaluation of operational inefficiencies in power generating units:a case study of Indian power plants. IEEE Transactions on Power Systems,1999,14(2):419–425
[94] Pahwa A,Feng X,Lubkeman D. Performance evaluation of electric distribution utilities based on data envelopment analysis. IEEE Transactions on Power System,2003,18(1):400-405
[95] Jha D K,Shrestha R. Measuring efficiency of hydropower plants in nepal using data envelopment analysis. IEEE Transactions on Power Systems, 2006,21(4):1502-1511
[96] Horowitz E,Sahni S. Fundamental of computer algorithms. New Delhi:Galgotia Publication,1996
[97]岳超源.决策理论与方法.北京:科学出版社,2003. 151-169,192-246
[98]电力工业部电力规划设计总院.电力系统设计手册.北京:中国电力出版社,1998. 179-189
[99]周云海.大停电事故后恢复控制技术研究:[博士学位论文].北京:清华大学,2001
[100]周德贵,巩北宁.同步发电机运行技术与实践,北京:中国电力出版社,1996. 75-121
[101]邢文训,谢金星.现代优化计算方法.北京:清华大学出版社,1999. 28-47
[102] Winter P. Steiner problem in networks:a survey. Networks,1987,17(1):129-167
[103]姚恩瑜,何勇,陈仕平.数学规划与组合优化.杭州:浙江大学出版社,2001. 154-164
[104]熊信银,吴耀武.遗传算法及其在电力系统中的应用.武汉:华中科技大学出版社,2002. 1-37
[105] Special issue on preferences of computational intelligence. Computational Intelligence,2004,20(2):109-443
[106] Brewka G. A rank based description language for qualitative preferences. Proceedings of the 16th European Conference on Artificial Intelligence,Valencia,Spain,Aug. 2004:303-307
[107] Wu F F,Liu W H. Detection of topology errors by state estimation. IEEE Transactions on Power Systems,1989,4(1):176-183
[108]王锡凡.现代电力系统分析.北京:科学出版社,2003. 284-289
[109] Adersen P, Petersen N C. A procedure for ranking efficient units in data envelopment analysis. Management Science,1993,39(10):1261-1264
[110] Chen Yao. Ranking efficient units in DEA. OMEGA,2004,32(6):213-219
[111] Mei Xue,Harker Patrick T. Note:ranking DMUs with infeasible super-efficiency DEA models. Management Science,2002,48(5):705-710
[112]刘文霞,刘晓茹,张建华,等.基于偏好DEA方法的配电通信网多种接入方式评估.电力系统自动化,2009,33(4):72-76
[113]刘艳.电力系统黑启动恢复及其决策支持系统的研究:[博士学位论文].保定:华北电力大学电力工程系,2007
[114] Talukdar Sarosh , Ramesh V C. A multi-agent technique for contingency constrained optimal power flows. IEEE Transactions on Power Systems,1994,9(2):855-861
[115] Jennings N R. Controlling cooperative problem solving in industrial multi-agent systems using joint intentions. Artificial Intelligence,1995,75(7):195-240
[116]刘青,程时杰.分布式问题求解系统及其在电力系统中的应用.电力系统自动化,1997, 21(1):50-52
[2] Andersson G,Donalek P,Farmer R,et al. Causes of the 2003 major grid blackouts in North America and Europe,and recommended means to improve system dynamic performance. IEEE Transactions on Power Systems,2005,20(4):1922-1928
[3] Makarov Y V,Reshetov V I,Stroev A,et al. Blackout prevention in the united states,Europe,and Russia. Proceedings of the IEEE,2005,93(11):1942-1955
[4]葛睿,董昱,吕跃春.欧洲11. 4大停电事故分析及对我国电网运行工作的启示.电网技术,2007,31(3):1-6
[5]陈向宜,陈允平,李春艳,等.构建大电网安全防御体系—欧洲大停电事故的分析及思考.电力系统自动化,2007,31(1):4-8
[6]王梅义,吴竞昌,蒙定中.大电网系统技术(第二版).北京:中国电力出版社,1995. 10-64
[7] Pereira L. Cascade to black [system blackouts]. IEEE Power and Energy Magazine, 2004,2(3):54-57
[8] Horowitz S H,Phadke A G. Boosting immunity to blackouts. Power and Energy Magazine,2003,1(5):47-53
[9] Roger Kearsley. Restoration in Sweden and experience gained from the blackout of 1983. IEEE Transactions on Power Systems,1987,2(2):422-428
[10] Salvati R,Sforna M,Pozzi M. Restoration project [Italian power restoration plan]. IEEE Power and Energy Magazine,2004,2(1):44-51
[11]唐斯庆,张弥,李建设,等.海南电网“9.26”大面积停电事故的分析与总结.电力系统自动化,2006,30(1):1-7,16
[12]何大愚.一年以后对美加“8.14”大停电事故的反思.电网技术,2004,28(21):1-5
[13] Adibi M M,Clelland P,Fink L,et al. Power system restoration - a task force report. IEEE Transactions on Power Systems,1987,2(2):271-277
[14] Adibi M M,Borkoski J N,Kafka R J. Power system restoration - the second task force report. IEEE Transactions on Power Systems,1987,2(4):927-933
[15] Wu F F,Monicelli A. Analytical tools for power system restoration - conceptual design. IEEE Transactions on Power Systems,1988,3(1):10-16
[16]房鑫炎,郁惟镛,熊惠敏,等.电力系统黑启动的研究.中国电力,2000,33(1):40-43,96
[17]刘隽,李兴源,许秀芳.互联电网的黑启动策略及相关问题.电力系统自动化,2004,28(5):93-97
[18] Adibi M M,Kafka R J. Power system restoration issues. IEEE Computer Application in Power,1991,4(2):19-24
[19] Adibi M M,Fink L H,Andrews C J,et al. Special considerations in power system restoration. IEEE Transactions on Power Systems,1992,7(4):1419-1424
[20] Adibi M M,Fink L H. Power system restoration planning. IEEE Transactions on Power Systems,1994,9(1):22-28
[21] Fink L H,Liou K L,Liu C C. From generic restoration actions to specific restoration stragies. IEEE Transactions on Power Systems,1995,10(2):745-751
[22]郭嘉阳,吴涛,张仁伟,等.华北电网“黑启动”试验研究.华北电力技术,2001,(5):3-18
[23]阮前途,王伟,黄玉,等.基于燃机机组的上海电网黑启动系列试验.电网技术,2006,30(2):19-22
[24] Lindenmeyer D,Dommel H W,Kundur P,et al. A framework for black start and power system restoration. Proceedings of the 2000 IEEE Canadian Conference on Electrical and Computer Engineering,Halifax,Nova Scotia,Canada,May. 2000:153-157
[25]刘艳,顾雪平,张丹.基于数据包络分析模型的电力系统黑启动方案相对有效性评估.中国电机工程学报, 2006,26(5):32-37,94
[26] Islam S,Chowdhury N. A case-based expert system for power system restoration. Proceedings of the 1999 IEEE Canadian Conference on Electrical and Computer Engineering,Edmonton,AB,Canada,May. 1999,2:1159-1163
[27] Germano Lambert-Torres,Luiz Eduardo Borges da Silva,Guilherme Moutinho Ribeiro,et al. An intelligent tool for power system restoration:an example using CESP. International Conference on Power System Technology,Kunming,China,Oct. 2000,2:1131-1136
[28] Chen Chao-Shun,Lin Chai-Hung,Tsai Hung-Ying. A rule based expert system with colored Petri net models for distribution system service restoration. IEEE Transactions on Power Systems,2002,17(4):1073-1080
[29] Salek K,Spanel U,Krost G. Flexible support for operators in restoring bulk power systems. CIGRE/IEEE PES International Symposium on Quality and Security of Electric Power Delivery Systems,Montreal,Canada,Oct. 2003:187-192
[30]王洪涛,刘玉田,丘夕照.基于分层案例推理的黑启动决策支持系统.电力系统自动化,2004,28(11):49-52
[31] Chin Hong-Chan,Su Yuh-Sheng. Application of the Ant-Based network for power system restoration. IEEE/PES Transmission and Distribution Conference and Exhibition:Asia and Pacific,Dalian,China,Aug. 2005:1-5
[32] Nagata T,Tao Y,Fujita H. An autonomous agent for power system restoration. IEEE Power Engineering Society General Meeting,Denver,CO,USA,June. 2004,1:1069-1074
[33] Solanki J M,Schulz N N,Gao Wenzhong. Reconfiguration for restoration of power systems using a multi-agent system. Power Symposium Proceedings of the 37th Annual North American,Ames,Iowa,USA,Oct. 2005:390-395
[34] Liu Dong,Chen Yunping,Shen Guang,et al. A multi-agent based approach for modeling and simulation of bulk power system restoration. IEEE/PES Transmission and Distribution Conference and Exhibition:Asia and Pacific,Dalian,China,Aug. 2005:1-6
[35] Nagata T,Tahara Y,Fujita H. An agent approach to bulk power system restoration. IEEE Power Engineering Society General Meeting,San Francisco,California,USA,Jun. 2005:1312-1317
[36] Li Ling,Liao Zhiwei,Huang Shaoxian,et al. A distributed model for power system restoration based on Ant Colony optimization algorithm. IEEE/PES Transmission and Distribution Conference and Exhibition:Asia and Pacific,Dalian,China,Aug. 2005:15-18
[37] Cooper M E,Adibi M M. Bulk power system restoration training teniques. IEEE Transactions on Power Systems,1993,8(1):191-197
[38] Miller G,Storey A,Vadari V,et al. Experiences using the dispatcher training simulator as a training tool. IEEE Transactions on Power Systems,1993,8(3):1126-1132
[39] Islam S,Chowdhury N. A case-based Windows graphic package for the education and training of power system restoration. IEEE Transactions on Power Systems,2001,16(2):181-187
[40] Sforna M,Bertanza V C. Restoration testing and training in Italian ISO. IEEE Transactions on Power Systems,2002,17(4):1258-1264
[41] Silva A,Vale Z,Ramos C. Cooperative training of power systems restoration techniques. Proceedings of the 13th International Conference on Intelligent Systems Application to Power Systems,Seoul,Korea,Nov. 2005:36-42
[42]张慎明,姚建国.调度员培训仿真系统(DTS)的现状和发展趋势.电网技术,2002,26(7):60-66
[43]孙宏斌,吴文传,张伯明.电网调度员培训仿真系统的新特性和概念扩展.电力系统自动化,2005,29(7):6-11
[44] Adibi M M,Borkoski J N,Kafka R J,et al. Frequency response of prime movers during restoration. IEEE Transactions on Power Systems,1999,14(2):751-756
[45] Jadid S,Salami A. Accurate model of hydroelectric power plant for load pickup during power system restoration. IEEE TENCON 2004,Chiang Mai,Thailand,Nov. 2004 (3):307-310
[46] Furukawa K,Izena A,Shimojo T,et al. Governor control study at the time of a black start. IEEE Power Engineering Society General Meeting,Denver,CO,USA,June. 2004 (2):1521-1526
[47] Nadira R,Dy Liacco T E,Loparo K A. A hierarchical interactive approach to electric power system restoration. IEEE Transactions on Power Systems,1992,7(3):1123-1131
[48]周云海,闵勇.恢复控制中的系统重构优化算法研究.中国电机工程学报,2003,23(4):67-70,188
[49] Ihara S,Schweppe F C. Physically based modeling of cold load pickup. IEEE Transactions on Power Apparatus and Systems,1981,100(9):4142-4150
[50] Chavali S,Pahwa A,Das S. A genetic algorithm approach for optimal distribution feeder restoration during cold load pickup. Proceeding of the 2002 Congress on Evolutionary Computation,Honolulu,Hawaii,USA,May. 2002:1816-1819
[51] Mohanty I. Ant algorithms for the optimal restoration of distribution feeders during cold load pickup. IEEE swarm Intelligence Symposium,Indianapolis,Indiana,USA,April. 2003:132-137
[52]周云海,闵勇.负荷的快速恢复算法研究.中国电机工程学报,2003,23(3):74-79
[53] Wang Qin,Ajjarapu V. A novel approach to implement generic load restoration in continuation-based quasi-steady-state analysis. IEEE Transactions on Power Systems,2005,20(1):516-518
[54] Huang S J,Huang C C. Adaptive approach to load shedding including pumped-storage units during underfrequency conditions. IEE Proceedings - Generation,Transmission and Distribution,2001,148(2):165-171
[55] Quaia S,Marchesin A,Marsigli B,et al. Using pumped storage loads in restoration paths:a field test in the Italian national grid. IEEE Transactions on Power Systems,2005,20(2):1580-1587
[56] Adibi M M,Alexander R W,Avramovic B. Overvoltage control during restoration. IEEE Transactions on Power Systems,1992,7(4):1464-1470
[57] Adibi M M,Milanicz D P. Reactive capability limitation of synchronous machines. IEEE Transactions on Power Systems,1994,9(1):29-40
[58] Adibi M M,Milanicz D P,Volkmann T L. Optimizing generator reactive power resources. IEEE Transactions on Power Systems,1999,14(1):319-324
[59] Adibi M M,Polyak R A,Griva I A,et al. Optimal transformer tap selection using modified barrier-augmented Lagrangian method. IEEE Transactions on Power Systems,2003,18(1):251-257
[60] Adibi M M,Alexander R W,Milanicz D P. Energizing high and extra-high voltage lines during restoration. IEEE Transactions on Power Systems,1999,14(3):1121-1126
[61]程改红,徐政.电力系统故障恢复过程中的过电压控制.电网技术,2004,28(11):29-33
[62]钱家骊,袁大陆,徐国政.对1000kV电网操作过电压及相位控制高压断路器的讨论.电网技术,2005,29(10):1-4,8
[63]张玉琼,顾雪平.基于随机统计分析的黑启动操作过电压的计算校验.电工技术学报,2005,20(5):92-97
[64]李膨源,顾雪平.基于神经网络的黑启动操作过电压快速预测.电网技术,2006,30(3):66-70
[65] Ketabi A,Ranjbar A M,Feuillet R. Analysis and control of temporary overvoltages for automated restoration planning. IEEE Transactions on Power Systems,2002,17(4):1121-1127
[66]程改红,徐政.电力系统故障恢复初期的谐波过电压问题.电网技术,2005,29(10):14-19
[67] Adibi M M , Milanicz D P. Protective system issues during restoration. IEEE Transactions on Power Systems,1995,10(3):1492-1497
[68] Sidhu T S,Tziouvaras D A,Apostolov A P,et al. Protection issues during system restoration. IEEE Transactions on Power Delivery,2005,20(1):47-56
[69]刘映尚,张碧华,周云海.黑启动过程中继电保护和安全自动装置的特性和运行.中国电力,2005,38(5):25-28
[70] Wunderlich S,Adibi M M,Fischl R,et al. An approach to standing phase angle reduction. IEEE Transactions on Power Systems,1994,9(1):470-478
[71] Hazarika D,Sinha A K. An algorithm for standing phase angle reduction for power system restoration. IEEE Transactions on Power Systems,1999,14(4):1213-1218
[72] Hazarika D,Sinha A K. Standing phase angle reduction for power system restoration. IEE Proceedings - Generation, Transmission and Distribution,1998,145(1):82-88
[73] Martins N,De Oliveira E J,Pereira J L R,et al. Reducing standing phase angles via interior point optimum power flow for improved system restoration [C]. IEEE PES Power Systems Conference and Exposition,New York,USA,Oct. 2004:404-408
[74]李阳坡,顾雪平,刘艳.电力系统黑启动过程中线路继电保护的配置与整定.电力系统自动化,2006,30(7):89-92,107
[75] Lu Ying,Kao Wen-Shiow,Chen Yung-Tien. Study of applying load shedding scheme with dynamic D-factor values of various dynamic load models to Taiwan power system. IEEE Transactions on Power Systems,2005,20(4):1976-1984
[76] Liu C C,Liou K L,Chu R F,et al. Generation capability dispatch for bulk power system restoration:a knowledge-based approach. IEEE Transactions on Power Systems,1993,8(1):316-325
[77]董张卓,焦建林,孙启宏.用层次分析法安排电力系统事故后火电机组恢复的次序.电网技术,1997,21(6):48-51,54
[78] Ketabi A,Asmar H,Ranjabar A M,et al. An approach for optimal units start-up during bulk power system restoration. Large Engineering Systems Conference on Power Engineering,Halifax,Nova Scotia,Canada,July. 2001:190-194
[79]刘艳,顾雪平.基于节点重要度评价的骨架网络重构.中国电机工程学报,2007,27(10):20-27
[80]周云海,刘映尚,胡翔勇.大停电事故后的系统网架恢复.中国电机工程学报,2008,28(10):32-36
[81]张志毅,陈允平,袁荣湘.电力系统负荷恢复问题的混合遗传算法求解.电工技术学报,2007,22(2):105-109
[82] NERC. NERC planning standards. North American Electric Reliability Council,1997
[83]中华人民共和国国家经济贸易委员会. DL/T 723-2000.电力系统安全稳定控制技术导则.北京:中国电力出版社,2001
[84]周云海,胡翔勇.恢复控制的一般策略和实例分析.三峡大学学报(自然科学版),2003,25(5):426-428
[85]张文亮,周孝信,白晓民,等.城市电网应对突发事件保障供电安全的对策研究.中国电机工程学报,2008,28(22):1-7
[86]胡键,郭志忠,刘迎春,等.故障恢复问题和发电机恢复排序分析.电网技术,2004,28(18):1-4,15
[87] Adibi M M,Martins N. Power system restoration dynamics issues. IEEE Power Energy Society General Meeting,Pittesburgh,Pennsylvania,USA,July. 2008:1-8
[88] De Mello F P,Westcott J C. Steam plant startup and control in system restoration. IEEE Transactions on Power Systems,1994,9(1):93-101
[89]钱颂迪,胡运权.运筹学.北京:清华大学出版社,1997. 236-239
[90]魏权龄.数据包络分析.北京:科学出版社,2004. 1-58
[91] Charnes A,Cooper W W,Rhodes E. Measuring the efficiency of decision making units. European Journal of Operations Research,1978,2(6):429-444
[92] Lewin A Y,Morey R C. Measuring the relative efficiency and output potential of public sector organizations:an application of data envelopment analysis. International Journal of Policy Analysis and Information Systems,1981,5(4):267-285
[93] Chitkara P,A data envelopment analysis approach to evaluation of operational inefficiencies in power generating units:a case study of Indian power plants. IEEE Transactions on Power Systems,1999,14(2):419–425
[94] Pahwa A,Feng X,Lubkeman D. Performance evaluation of electric distribution utilities based on data envelopment analysis. IEEE Transactions on Power System,2003,18(1):400-405
[95] Jha D K,Shrestha R. Measuring efficiency of hydropower plants in nepal using data envelopment analysis. IEEE Transactions on Power Systems, 2006,21(4):1502-1511
[96] Horowitz E,Sahni S. Fundamental of computer algorithms. New Delhi:Galgotia Publication,1996
[97]岳超源.决策理论与方法.北京:科学出版社,2003. 151-169,192-246
[98]电力工业部电力规划设计总院.电力系统设计手册.北京:中国电力出版社,1998. 179-189
[99]周云海.大停电事故后恢复控制技术研究:[博士学位论文].北京:清华大学,2001
[100]周德贵,巩北宁.同步发电机运行技术与实践,北京:中国电力出版社,1996. 75-121
[101]邢文训,谢金星.现代优化计算方法.北京:清华大学出版社,1999. 28-47
[102] Winter P. Steiner problem in networks:a survey. Networks,1987,17(1):129-167
[103]姚恩瑜,何勇,陈仕平.数学规划与组合优化.杭州:浙江大学出版社,2001. 154-164
[104]熊信银,吴耀武.遗传算法及其在电力系统中的应用.武汉:华中科技大学出版社,2002. 1-37
[105] Special issue on preferences of computational intelligence. Computational Intelligence,2004,20(2):109-443
[106] Brewka G. A rank based description language for qualitative preferences. Proceedings of the 16th European Conference on Artificial Intelligence,Valencia,Spain,Aug. 2004:303-307
[107] Wu F F,Liu W H. Detection of topology errors by state estimation. IEEE Transactions on Power Systems,1989,4(1):176-183
[108]王锡凡.现代电力系统分析.北京:科学出版社,2003. 284-289
[109] Adersen P, Petersen N C. A procedure for ranking efficient units in data envelopment analysis. Management Science,1993,39(10):1261-1264
[110] Chen Yao. Ranking efficient units in DEA. OMEGA,2004,32(6):213-219
[111] Mei Xue,Harker Patrick T. Note:ranking DMUs with infeasible super-efficiency DEA models. Management Science,2002,48(5):705-710
[112]刘文霞,刘晓茹,张建华,等.基于偏好DEA方法的配电通信网多种接入方式评估.电力系统自动化,2009,33(4):72-76
[113]刘艳.电力系统黑启动恢复及其决策支持系统的研究:[博士学位论文].保定:华北电力大学电力工程系,2007
[114] Talukdar Sarosh , Ramesh V C. A multi-agent technique for contingency constrained optimal power flows. IEEE Transactions on Power Systems,1994,9(2):855-861
[115] Jennings N R. Controlling cooperative problem solving in industrial multi-agent systems using joint intentions. Artificial Intelligence,1995,75(7):195-240
[116]刘青,程时杰.分布式问题求解系统及其在电力系统中的应用.电力系统自动化,1997, 21(1):50-52