微电网故障重构方法研究
|
摘要
随着我国经济的飞速发展和工业化进程的不断加快,除了对传统互联电网的电力供应提出更高的要求外,对微电网(Microgrid)的需求也与日俱增。微电网包括各种小型独立电网和接入分布式电源(Distributed Generation, DG)的配电网。微电网与传统互联大电网在网络结构和供电方式上均存在较大的差异,因此,在研究故障重构问题时所考虑的因素和关注的侧重点也不尽相同。本文以舰船电力系统(Shipboard Power System, SPS)和接入分布式电源配电网为例,进行故障重构研究。论文在回顾舰船电力系统和含分布式电源配电网故障重构研究现状的基础上,对目前已有的研究方法和成果进行了概述和总结,归纳了目前各类方法中所存在的一些不足和局限性。针对舰船电力系统故障重构问题分别采用集中式和分布式等多种方法进行对比研究,并将分布式的多代理系统(Multi-Agent System, MAS)技术推广应用于含分布式电源配电网的故障重构研究。全文由以下几个部分组成：首先,建立了舰船电力系统故障重构的优化目标函数和约束条件体系,并采用二进制粒子群优化算法(Binary Particle Swarm Optimization, BPSO)进行优化求解。通过无向图描述舰船电力系统的拓扑结构,采用邻接矩阵存储网络拓扑信息。在进行优化求解时,直接对负载供电状态和少数关键电缆通断状态进行编码,有效地降低编码长度。采用深度优先搜索算法在系统发生故障后对舰船电力系统进行连通性分析,以确定粒子编码的取值范围,很大程度上缩小算法的搜索空间,提高收敛速度。其次,将分支定界法(Branch and Bound Method)应用于舰船电力系统的故障重构研究,建立舰船电力系统的故障重构的数学规划模型。在总结前人研究工作的基础上,对文献中已有的数学模型进行适当改进。结合实际情况,将舰船电力系统的主网络列入重构范围,可以提供更为灵活的供电结构,提高系统供电可靠性。仿真结果表明采用数学规划进行舰船电力系统的故障重构,能够保证解的稳定性和可靠性。再次,介绍了代理、多代理系统技术的发展历史以及相关的基本概念、体系结构等,综述了多代理系统技术在电力系统应用的研究现状和发展趋势。介绍了多代理系统开发软件平台JADE(Java Agent Development Framework),简述了基于JADE平台的多代理系统程序设计的一般过程。第四部分,提出一种分布式的MAS模型来实现舰船电力系统的故障重构,在保障高优先级负载供电的前提下尽可能地恢复系统供电。论文所提出的MAS模型中各代理都具备一定的推理能力,能够根据不同的环境做出合理的决策。采用Java程序设计语言和JADE平台设计MAS程序。最后通过典型的故障算例验证所提出MAS模型以及重构策略的可行性和有效性。最后,提出一种由母线代理(Bus Agent, BA)组成的完全分布式MAS,实现含分布式电源配电网的故障重构功能。论文所提出的MAS中,每一个BA都具备独立引导故障重构的能力,BA相互之间进行通讯、协作共同完成故障重构任务。为保障BA间通讯的有效进行,制定了深度优先通讯机制。该MAS模型能处理单一故障和极端情况下的连锁故障。采用Java程序设计语言和JADE平台设计MAS。通过典型的故障算例验证了该MAS的有效性。
With the rapid development of economy and ceaseless acceleration in industrialized process, the request for microgrid (MG) is increasing rapidly apart from the higher requirements for the power supplied by the conventional interconnected power grid. MG consists of various kinds of small stand-alone power systems and the distribution networks with distributed generation (DG) integration. There is significant difference of structures and power supply modes between microgrid and interconnected power system. Therefore, when fault restoration problems are studied, the emphases in the two types systems are different. This thesis takes shipboard power system (SPS) and the distribution networks with DGs for instance to study the fault restoration problem.The current research methods and achieved results in the field of fault restoration in shipboard power system and distribution network with DGs are summarized at first. Then the insufficiency and the flaw of the existing methods are pointed out. Compared various methods for the fault restoration rearch of SPS, this thesis applied the multi-agent system (MAS) technology into the restoration problem of distribution network with DGs. The structure of the whole thesis is listed as follows:Firstly, the fault restoration optimization model of independent shipboard power system is proposed, and the Binary System Particle Swarm Optimization (BPSO) is used for the optimization problem solution. Undirected graph is used to describe the network topology of the shipboard power system, and the adjacency matrix is used to store the network topology information. The encoding method of this algorithm is based on the power state of all loads, the opening and closing state of important cables, which can reduce the encoding length effectively. Based on depth first search after fault, the network connectivity is analyzed in order to confirm the range of particle code value, which can shorten the searching space and improve the convergence speed of the algorithm.Secondly, the mathematic programming model of independent shipboard power system is proposed and the Branch and Bound Method is used for the optimization problem solution. Mathematical programming method proposed in the early literature has been improved in this thesis. According to the actual situation, considering the reconfiguration of major network can make the network structure more flexible, and increase reliability of the SPS. The simulation results indicate that using mathematical programming to solve the fault restoration problem can obtain stable optimal solution.Thirdly, the basic concepts, architectures, and development history of distributed artificial intelligence, agent, and multi-agent system technology are introduced. The current situation and the developing trend of the application of MAS technology in the electric power system are summarized. The Java Agent development framework (JADE) and its programming process are introduced in detail.Fourthly, a prototype of MAS is proposed to reconfigure the SPS in order to maximize the number of served loads with highest priority. Agents of the MAS have the ability of illation, and makes reasonable decisions according to different environments. The MAS is implemented using Java programming language and JADE. The simulation results of typical SPS fault restoration cases demonstrate the feasibility and the advantages of the proposed MAS.Finally, a fully decentralized MAS has been proposed for load restoration of power distribution network with DGs. The proposed multi-agent system consists of bus agents (BAs). Every BA in the MAS has the ability to lead the restoration work independently. The restoration work could be completed by the communication and cooperation among the BAs. In order to ensure smooth communication, a depth-first communication mechanism (DFCM), similar to the process of depth-first search (DFS), is proposed. The MAS is capable of dealing with a single fault or cascading failures. The proposed multi-agent system is implemented based on JADE. The simulation results of typical fault cases verifiy the feasibility of the proposed MAS.
With the rapid development of economy and ceaseless acceleration in industrialized process, the request for microgrid (MG) is increasing rapidly apart from the higher requirements for the power supplied by the conventional interconnected power grid. MG consists of various kinds of small stand-alone power systems and the distribution networks with distributed generation (DG) integration. There is significant difference of structures and power supply modes between microgrid and interconnected power system. Therefore, when fault restoration problems are studied, the emphases in the two types systems are different. This thesis takes shipboard power system (SPS) and the distribution networks with DGs for instance to study the fault restoration problem.The current research methods and achieved results in the field of fault restoration in shipboard power system and distribution network with DGs are summarized at first. Then the insufficiency and the flaw of the existing methods are pointed out. Compared various methods for the fault restoration rearch of SPS, this thesis applied the multi-agent system (MAS) technology into the restoration problem of distribution network with DGs. The structure of the whole thesis is listed as follows:Firstly, the fault restoration optimization model of independent shipboard power system is proposed, and the Binary System Particle Swarm Optimization (BPSO) is used for the optimization problem solution. Undirected graph is used to describe the network topology of the shipboard power system, and the adjacency matrix is used to store the network topology information. The encoding method of this algorithm is based on the power state of all loads, the opening and closing state of important cables, which can reduce the encoding length effectively. Based on depth first search after fault, the network connectivity is analyzed in order to confirm the range of particle code value, which can shorten the searching space and improve the convergence speed of the algorithm.Secondly, the mathematic programming model of independent shipboard power system is proposed and the Branch and Bound Method is used for the optimization problem solution. Mathematical programming method proposed in the early literature has been improved in this thesis. According to the actual situation, considering the reconfiguration of major network can make the network structure more flexible, and increase reliability of the SPS. The simulation results indicate that using mathematical programming to solve the fault restoration problem can obtain stable optimal solution.Thirdly, the basic concepts, architectures, and development history of distributed artificial intelligence, agent, and multi-agent system technology are introduced. The current situation and the developing trend of the application of MAS technology in the electric power system are summarized. The Java Agent development framework (JADE) and its programming process are introduced in detail.Fourthly, a prototype of MAS is proposed to reconfigure the SPS in order to maximize the number of served loads with highest priority. Agents of the MAS have the ability of illation, and makes reasonable decisions according to different environments. The MAS is implemented using Java programming language and JADE. The simulation results of typical SPS fault restoration cases demonstrate the feasibility and the advantages of the proposed MAS.Finally, a fully decentralized MAS has been proposed for load restoration of power distribution network with DGs. The proposed multi-agent system consists of bus agents (BAs). Every BA in the MAS has the ability to lead the restoration work independently. The restoration work could be completed by the communication and cooperation among the BAs. In order to ensure smooth communication, a depth-first communication mechanism (DFCM), similar to the process of depth-first search (DFS), is proposed. The MAS is capable of dealing with a single fault or cascading failures. The proposed multi-agent system is implemented based on JADE. The simulation results of typical fault cases verifiy the feasibility of the proposed MAS.
引文
[1]杨秀霞,张晓锋,张毅.独立电力系统故障恢复现状及发展趋势[J].继电器,2004,32(19)：74-79.
[2]焦寨军,沈兵,李红江.几种遗传算法在舰船电力系统网络重构中应用及比较[J].微计算机信息,2005,21(34)：184-187.
[3] K. L. Bulter. An ONR young investigator project-predietive reconfiguration of shipboard powers ystems [C]. IEEE Power Engineering Society General Meeting, 2003,1:106-107.
[4]杨秀霞,张晓锋,张毅.大型舰船电力系统网络重构研究[J].海军工程大学学报,2004,16(2)：44-47.
[5] EPRI US, EDF R&D. Profiling and Mapping of Intelligent Grid R&D Programs [R]. EPRI, Palo Alto, CA, USA and EDF R&D, Clamart, France:2006.
[6] European Commission. European Technology Platform Smart Grids:Vision and Strategy for Europe's Electricity Networks of the Future [R/OL]. Luxembourg:Office for Official Publications of the European Commission,2006 [2009-12-18]. http://ec.europa.eu/research/energy/pdf/smartgrids_en.pdf.
[7] Commission of the European Communities. Green Paper:A Europearl Strategy for Sustainable, Competitive and Secure Energy [R]. Brussels, Belgium:Communities, Commission of the European,2006.
[8]余贻鑫,栾文鹏.智能电网[J].电网与清洁能源,2009,25(1)：1-5.
[9]刘振亚.智能电网技术[M].北京：中国电力出版社,2010.
[10]王成山,王守相,郭力.我国智能配电技术展望[J].南方电网技术.2010,4(1)：18-22.
[11]战杰,肖静,赵义术.分布式电源和微网在智能配电网自愈功能中的作用分析[J].山东电力高等专科学校学报.2010,13(2)：33-36.
[12]黄盛.智能配电网通信业务需求分析及技术方案[J].电力系统通信,2010,31(12)：10-12,17.
[13]陆一鸣,刘东,柳劲松,等.智能配电网信息集成需求及模型分析[J].电力系统自动化,2010,34(8)：1-4,96.
[14]贾东梨,孟晓丽,宋晓辉.智能配电网自愈控制技术体系框架研究[J].电网与清洁能源,2011,27(2)：14-18.
[15]焦彦军,苑峰,苑玉山.“自愈”性配电网自动化系统建设研究[C].中国高等学校电力系统及其自动化专业第二十五届学术年会,2009.
[16] T. Nagata, H. Sasaki, R. Yokoyama. Power system restoration by joint usage of expert system and mathematical programming approach [J]. IEEE Transactions on Power Systems,1995,10(3):1473-1479.
[17] N. D. R. Sarma, V. C. Prasad, K. S. Prakasa Rao, V. Sankar. A new network reconfiguration technique for service restoration in distribution networks [J]. IEEE Transactions on Power Delivery,1994,9(4):1936-1942.
[18]张玉眷,杨成峰,彭亚楠,等.配电网非故障区恢复供电方法研究[J].供用电,2007,24(5)：22-24.
[19]李海锋,张尧,钱国基,等.配电网故障恢复重构算法研究[J].电力系统自动化,2001,25(8)：22-24.
[20]郑俊健.配电网故障恢复方法研究[J].科技资讯,2010,(21)：139-140.
[21]张玉春,杨成峰,彭亚楠,等.配电网故障恢复的方法[J].中国设备工程,2008,(4)：49-51.
[22] H. H. Zeineldin, K. Bhattacharya, E. F. El-saadany, et al. Impact of intentional islanding of distributed generation on electricity market prices [J]. IEE Proceedings of Generation, Transmission and Distribution,2006,153(2):147-154.
[23]卢志刚,董玉香.含分布式电源的配电网故障恢复策略[J].电力系统自动化,2007,31(1)：89-92.
[24]易新,陆于平.分布式发电条件下的配电网孤岛划分算法[J].电网技术,2006,
30(7)：50-54.
[25]尹丽燕,于继来.多时间段落的配电网络动态重构[J].中国电机工程学报,2002,22(7)：44-48,80.
[26]刘扬,杨建军,魏立新.改进遗传模拟退火算法在配电网络重构中的应用[J].电力系统及其自动化学报,2004,16(5)：39-42,74.
[27]金丽成,邱家驹.基于CMAC神经网络的配网重构模型[J].浙江大学学报,2004,38(6)：784-788.
[28]韩学军,陈鹏,国新凤,等.基于潮流计算的配电网重构方法[J].电网技术,2007,31(17)：60-63.
[29]居荣,唐小波,鞠勇,等.用于减小供电成本的配电网络重构[J].电气应用,2007,26(1)：42-44,64.
[30]魏智博,刘艳,顾雪平.基于DPSO算法以负载恢复为目标的网络重构[J].电力系统及其自动化学报,2007,31(1)：38-42.
[31]叶远波.故障后配网系统网络重构的研究[J].华东电力,2002,(9)：60-64.
[32]张玉春,杨成峰,曹海英,等.配电网络故障恢复重构的改进遗传算法[J].华中电力,2007,20(4)：18-22.
[33]回志澎,冀路明,陈新刚,等.现代舰船区域配电[J].船舶工程,2005,27(6)：63-67.
[34] R. W. Ashton, J. G. Ciezki. A Novel Power Systems Program at the Naval Post graduate School [J]. IEEE Transactions on Power Systems,1997,12(2):515-520.
[35]陈虹.基于直流配电系统的船舶综合电力系统[J].舰船科学技术,2005,27(增)：31-37.
[36]高磊,吴学智.舰船D-ZED环境PLC信号衰减分析[J].舰船电子工程,2007,27(4)：145-148.
[37]王征,王家林,姚刚等.基于多Agent的船舶电力系统故障诊断系统设计[J].船电技术,2010,30(5)：1-6.
[38]张毅,杨秀霞.舰船电力系统网络重构研究综述[J].电工技术学报,2005,20(8)：
1-6.
[39] K. L. Bulter, N. D. R. Sarma, C. Whitcomb, et al. Shipboard systems deploy automated protection [J]. IEEE Computer Applications in Power,1998,11(2):31-36.
[40]吕昊,叶志浩,纪锋,等.开关动作次数最少目标函数的舰船电力系统重构[J].中国修船,2009,22(1)：26-29.
[41]刘维亭,邱赞.网络重构法在舰船区域配电系统中的应用研究[J].舰船科学技术,2009,31(2)：53-57.
[42]王文明,刘维亭,朱志字,等.基于图论理论的舰船配电网故障恢复算法[J].船海工程,2008,37(5)：86-89,94.
[43] S. Srivastava, K. L. Butler-Purry. Expert-system Method for Automatic Reconfigura-tion for Restoration of Shipboard Power System [J]. IEE Proceedings Generation, Transmission and Distribution,2006,153(3):253-260.
[44] S. K. Srivastava, K. L. Butler-Purry, N. D. R. Sarma. Shipboard Power Restored for Aetive Duty [J]. IEEE Computer Applications in Power.2002,15(3):16-23.
[45] Zhiping Ding, Srivastava. S, Cartes. D. Expert System based Dynamic Load Shedding Scheme for Shipboard Power Systems [C]. In:41st IAS Annual Conference Record of the 2006. Oct.2006:1338-1344.
[46] K. L. Butler, N. D. R. Sarma. Intelligent Network Reconfiguration of Shipboard Power Systems [C]. IEEE Power Engineering Society General Meeting.2003,4: 2435-2439.
[47] Fan Ji-Yuan, Zhang Lan, J. D. McDonald. Distribution Network Reconfiguration: Single Loop Optimization [J]. IEEE Transactions on Power Systems,1996,11 (3): 1643-1647.
[48] N. D. R. Sarma, K. S. Prakasa Rao. A New 0-1 Integer Programming Method of Feeder Reconfiguration for Loss Minimization in Distribution Systems [J]. Electric Power System Research,1995,33(2):125-131.
[49] A. Abur. Modified linear programming method for distribution system reconfigure-
ation[J]. International Journal of Electrical Power and Energy System,1996,18(7): 469-474.
[50] T. P. Wagner, A. Y. Chikhani, R. Hackam. Feeder reconfiguration for loss reduction: An application of distribution automation [J]. IEEE Transactions on Power Delivery, 1991,6(4):1922-1933.
[51] K. Aoki, T. Ichimori, M. Kanezashi. Normal State Optimal Load Allocation in Distribution Systems [J]. IEEE Transactions on Power Delivery,1987,2(1): 147-155.
[52] K. L. Butler, N. D. R. Sarma, V. R. Prasad. A New Method of Network Reconfiguration for Service Restoration in Shipboard Power Systems [C]. IEEE Transmission and Distribution Conference.1999,2:658-662.
[53] K. L. Butler, N. D. R. Sarma, V. R. Prasad. Network reconfiguration for service restoration in shipboard power distribution systems [J]. IEEE Transactions on Power System,2001,16(4):653-661.
[54] K. L. Butler, N. D. R. Sarma. Self-Healing Reconfiguration for Restoration of Naval Shipboard Power Systems [J]. IEEE Transactions on Power Systems,2004, 19(2):754-762.
[55] K. Nara, A. Shiose, M. Kitagawa. Implementation of Genetic Algorithm for Distribution Systems Loss Minimum Reconfiguration [J]. IEEE Transactions on Power Systems,1992,7(3):1044-1051.
[56] W. P. Luan, M. R. Irving, J. S. Daniel. Genetic Algorithm for Supply Restoration and Optimal Load Shedding in Power System Distribution Networks [J]. IEE Proc-Gener, Transmand Distrib,2002,149(2):145-151.
[57]刘莉,陈学允.基于模糊遗传算法的配电网络重构[J].中国电机工程学报,2000,20(2)：66-69.
[58]李晓明,黄彦浩,尹项根.基于改良策略的配电网重构遗传算法[J].中国电机工程学报,2004,24(2)：49-54.
[59]毕鹏翔,刘健,等.配电网络重构的改进遗传算法[J].电力系统自动化,2001,25(9)：53-55.
[60]盛四清,梁志瑞,等.基于遗传算法的地区电网停电恢复[J].电力系统自动化,2002,26(2)：57-61.
[61]余贻鑫,丘炜,刘若沁.基于启发式算法与遗传算法的配电网重构[J].电网技术,2001,25(11)：19-22.
[62]余贻鑫,段刚.基于最短路算法和遗传算法的配电网络重构[J].中国电机工程学报,2000,20(9)：44-49.
[63]杨秀霞,张晓锋,张毅,等.基于启发式遗传算法的舰船电力系统网络重构研究[J].中国电机工程学报,2003,23(10)：42-46.
[64]杨秀霞,张晓锋,张毅,等.免疫遗传算法在舰船电力系统供电恢复中的应用研究[J].中国电机工程学报,2004,24(9)：80-86.
[65]杨秀霞,张晓锋,张毅,等.基于加速遗传算法的舰船电力系统故障恢复[J].电工技术学报,2005,20(5)：53-57.
[66]何芳,蔡兴国.基于改进遗传算法的舰船电力系统网络重构[J].电工技术学报,2006,21(9)：25-30.
[67]庄肖波,孟思齐,刘维亭.基于混沌遗传算法的舰船电力系统故障恢复[J].继电器,2007,35(21)：39-42.
[68]何祖军,王文明,刘维亭.基于混沌遗传算法的舰船区域配电系统故障恢复算法[J].船电技术,2008,28(6)：380-382.
[69]王敏,刘维亭.混沌遗传算法在船舶电力系统供电恢复中的应用研究[J].江苏科技大学学报,2008,22(5)：6-10.
[70]刘大宝,夏立,王征.多智能体遗传算法在船舶电力网络重构中的应用[J].中国航海,2011,34(4)：39-44,66.
[71]黄席樾,向长城,殷礼胜.现代智能算法理论及应用[M].北京：科学出版社,2005.
[72]靳现林,王建生,韩蕾.一种改进粒子群优化算法的配电网重构[J].东北电力
技术,2007,(10)：11-15.
[73]许立雄,吕林,刘俊勇.基于改进粒子群优化算法的配电网络重构[J].电力系统自动化,2006,30(7)：27-30,79.
[74]卢志刚,杨国良,张晓辉,文莹.改进二进制粒子群优化算法在配电网络重构中的应用[J].电力系统保护与控制,2009,37(7)：30-34.
[75]靳晓凌,赵建国.基于改进二进制粒子群优化算法的负载均衡化配电网重构[J].电网技术,2005,29(23)：40-43.
[76]李振坤,陈星莺,余昆,等.配电网重构的混合粒子群算法[J].中国电机工程学报,2008,28(31)：35-41.
[77]吕林,王佳佳,刘俊勇,等.基于多粒子群分层分布式优化的配电网重构[J].电力系统保护与控制,2009,37(19)：56-60,68.
[78]刘自发,葛少云,余贻鑫.一种混合智能算法在配电网络重构中的应用[J].中国电机工程学报,2005,25(15)：73-78.
[79]白丹丹,刘观起,郭丽.基于改进粒子群算法的配电网重构的研究[J].华北电力大学学报,2006,33(6)：20-23.
[80]肖鲲,黄挚雄.多智能体粒子群算法在配电网络重构中的应用[J].计算机工程与应用,2010,46(8)：221-224,227.
[81]李军军,王锡淮,肖建梅.基于离散微粒群优化算法的舰船电力系统网络重构[J].中国电机工程学报,2006,26(25)：6-10.
[82]王锡淮,李军军,肖建梅.基于梯度DPSO算法在舰船电力系统网络重构[J].电工技术学报,2007,22(12)：140-145.
[83]王锡淮,李军军,肖建梅.求解舰船电力系统网络重构的贪婪DPSO算法[J].控制与决策,2008,23(2)：157-161.
[84]陈雁,孙海顺,文劲宇,等.改进粒子群算法在船舶电力系统网络重构中的应用[J].电力自动化设备,2011,31(3)：29-34,39.
[85]刘大宝,夏立,王征.多Agent粒子群算法在船舶电力网络重构中的应用[J].船电技术,2011,31(11)：42-47.
[86]李军军,许波桅,甘世红,等.基于贪婪度表的DPSO求解舰船电力系统网络重构[J].电工技术学报,2011,26(5)：146-151.
[87]蔡自兴,徐光祜.人工智能及其应用[M].北京：清华大学出版社,2010.
[88]陈根军,王磊,唐国庆.基于蚁群最优的配电网络重构算法[J].电力系统及其自动化学报,2001,13(2)：48-53.
[89]甘学涛,宋喜,王志刚,等.基于蚁群算法的配电网络重构模型及其应用[J].西北农林科技大学学报,2005,33(5)：157-160.
[90]汪超,马红卫,胡志坚,等.基于蚁群系统(ACS)的配电网重构[J].继电器,2006,34(23)：35-38,43.
[91]徐延炜,贾嵘.基于人工免疫思想的蚁群算法(AIACS)在配电网重构中的[J].电力系统保护与控,2010,38(18)：89-93
[92]黄健,张尧,李绮雯.蚁群算法在配电网重构的应用[J].电力系统及其自动化学报,2007,19(4)：59-64.
[93]李哲,夏立.改进蚁群算法求解船舶电力系统故障重构问题[J].电力系统及其自动化学报,2009,21(2)：47-52.
[94]王征,王永骥,李哲.基于改进蚁群算法的船舶电力系统故障重构研究[J].计算技术与自动化,2010,29(1)：1-4.
[95] L. N. de Castro, F. J. Von Zuben. Learning and optimization using the clonal selection principle [J]. IEEE Transactions on Evolutionary Computation,2002,6(3): 239-251.
[96]王击,罗安,张敏,等.修正克隆遗传算法在配电网络重构中的应用[J].湘潭矿业学院学报,2004,19(1)：80-83.
[97]何友林,张洪涛,郭创新,等.抗体克隆算法在配电网络重构中的应用[J].继电器,2006,34(16)：22-26,43.
[98]周辉,王击,罗安,等.克隆遗传算法与模拟退火算法相结合的配电网络重构[J].继电器,2007,35(7)：41-45.
[99]邹凤娇,王击,徐留杰.基于免疫克隆遗传算法的配电网络重构[J].微计算机
信息,2009,25(7)：222-224.
[100]张利民,马强,李振坤,等.基于禁忌克隆遗传算法的配电网故障恢复重构[J].电力系统及其自动化学报,2010,22(1)：60-64.
[101]谢林峰,姚强.基于自适应免疫克隆选择算法的配电网重构[J].南方电网技术,2011,5(6)：81-85.
[102]朱志宇,刘维亭,庄肖波.基于克隆算法的舰船电力系统故障恢复[J].电工技术学报,2009,12(1)：155-170.
[103]黄巧亮,王文明,刘维亭,等.基于克隆算法的舰船区域配电系统故障恢复算法[J].舰船科学技术,2009,31(11)：97-101.
[104]王敏,刘维亭.免疫克隆选择算法在船舶电力系统故障恢复中的应用研究[J].电力系统保护与控制,2009,37(1)：19-23,60.
[105] Chiang Hsiao-Dong, Jean-Jumeau, Rene. Optimal Network Reconfigurations in Distribution Systems:Part 1:A New Formulation and a Solution Methodology [J]. IEEE Transactions on Power Delivery,1990,5(4):1902-1909.
[106] Wang Jin-Cheng, Chiang Hsiao-Dong, G. R. Daring. An Efficient Algorithm for Real-time Network Reconfiguration in Large Scale Unbalanced Distribution Systems [J]. IEEE Transactions on Power Systems,1996,11(1):511-517.
[107] Jeon Young-Jae, Kim Jae-Chul, Kim Jin-O, et al. An Efficient Simulated Annealing Algorithm for Network Reconfiguration in Large-scale Distribution Systems [J]. IEEE Transactions on Power Delivery,2002,17(4):1070-1078.
[108] Brown R. E. Distribution Reliability Assessment and Reconfiguration Optimization [C]. Proceedings of the IEEE Power Engineering Society Transmission and Distribution Conference,2001,2:994-999.
[109]胡敏羞,陈元.配电系统最优网络重构的模拟退火算法[J].电力系统自动化,1994,18(2)：24-28.
[110]陈根军,李线洗,唐国庆.基于Tabu搜索的配电网络重构算法[J].中国电机工程学报,2002,22(10)：28-33.
[111]左飞,周家启.TS算法在配电网络重构中的应用[J].电力系统自动化学报,2004,16(1)：66-69.
[112]葛少云,刘自发,余贻鑫.基于改进禁忌搜索的配电网重构[J].电网技术,2004,28(23)：22-26.
[113]张栋,张刘春,傅正财.基于改进禁忌算法的配电网络重构[J].电工技术学报,2005,20(11)：60-64.
[114]张忠会,李曼丽,熊宁,等.基于改进禁忌搜索的配电网重构[J].继电器,2007,35(10)：4144.
[115]熊宁,程浩忠.基于开关组的禁忌算法在配电网动态重构中的应用[J].电力系统自动化,2008,32(11)：56-60.
[116]王林川,梁栋,于冬皓,等.基于遗传和禁忌搜索混合算法的配电网重构[J].电力系统保护与控制,2009,37(6)：27-31.
[117]王林川,李漫,张木子,等.基于蚁群禁忌搜索混合算法的配电网重构[J].吉林电力,2010,38(5)：34-36.
[118] H. Kim, Y. Ko, K. H. Jung. Artificial Neural-Network Based Feeder Reconfiguration for Loss Reduction in Distribution Systems [J]. IEEE Transactions on Power Delivery,1993,8(3):1356-1366.
[119] M. A. Kashem, G. B. Jasmon, A. Mohamed, et al. Artificial Neural Network Approach to Network Reconfiguration for Loss Minimization in Distribution Networks [J]. International Journal of Electrical Power and Energy System,1998, 20(4):247-258.
[120] K. L. Bulter, N. D. R. Sarma. General Reconfiguration Methodology for AC Radial Shipboard Power Systems [C]. IEEE 2000 Power Engineering Society Winter Meeting.2000,2:1226-1230.
[121] J. A. Momoh, J. Z. Zhu, S. S. Kaddah. Optimal Load Shedding Study of Naval-ship Power System Using the Everett Optimization Technique [J]. Electric Power Systems Research,2002,60(3):145-152.
[122] S. K. Srivastava, K. L. Butler-Purry. A Pre-hit Probabilistic reconfiguration methodology for shipboard Power systems [C]. IEEE Electric Ship Technologies Symposium,2005:99-104.
[123] S. K. Srivastava, K. L. Butler-Purry. A Probability Based Predictive Reconfiguration Method for Shipboard Power Systems [C]. IEEE Probabilistic Methods Applied to Power Systems International Conference,2004:813-818.
[124] K. L. Butler, N. D. R. Sarma. Preventive self-healing shipboard power distribution systems [C]. IEEE Power Engineering Society General Meeting,2005,3: 2443-2444.
[125] S. K. Srivastava, H. Xiao, K. L. Butler-Purry. Multi-agent system for automated service restoration of shipboard power systems [J]. Journal of Computer Information Systems,2003,44(1):119-123.
[126] L. Sun, D. Cartes. A multi-Agent system for reconfiguration of shipboard power systems [J]. Transactions on International Association of Mechanical Engineers, 2004,1 (3):425-431.
[127] A. Feliachi, K. Schoder, S. Ganesh, H. J. Lai. Distributed Control Agent Approach to Energy Management in Electric Shipboard Power System [C]. IEEE Power Engineering Society General Meeting,2006.
[128] J. M. Solanki, N. N. Schulz, W. Gao. Reconfiguration for Restoration of Power Systems Using a Multi-agent System [C]. Proceedings of the 37th Annual North American Power Symposium,2005:390-395.
[129] J. A. Momoh, O. S. Diouf. Optimal Reconfiguration of the Navy Ship Power System Using Agents [C]. Proceedings of the IEEE Power Engineering Society Transmission and Distribution Conference,2006:562-567.
[130] G. Morejon, S. K. Srivastava, D. A. Cartes. Integration Virtual Test Bed and JADE Agent Platform Using CORBA for Reconfiguration of Shipboard Power Systems [C]. IEEE Power Engineering Society General Meeting,2006:18-22.
[131] J. M. Solanki, N. N. Schulz. Using intelligent multi-agent systems for shipboard power systems reconfiguration [C]. in Proceedings of the 13th International Conference on Intelligent Systems Application to Power Systems,2005:212-214.
[132] Huang Kai, S. K. Srivastava, D. A. Cartes, et al. Intelligent Agents applied to reconfiguration of mesh structured power systems [C]. International Conference on Intelligent Systems Applications to Power Systems (ISAP), Kaohsiung, Taiwan, China,2007.
[133] Huang Kai. Shipboard power system reconfiguration using multi-agent system [D]. Florida:The Florida State University,2007.
[134] J. M. Solanki, S. Khushalani, N. N. Schulz. A multi-agent solution to distribution systems restoration [J]. IEEE Transactions on Power Systems,2007,22(3): 1026-1034.
[135] T. Nagata, H. Sasaki. A multi-agent approach to power system restoration [J]. IEEE Transactions on Power Systems,2002,17(2):457-462.
[136] J. A. Momoh. Navy ship power system restoration using multi-agent approach [C]. IEEE Power Engineering Society General Meeting, Montreal, Quebec, Canada, 2006:14-18.
[137] K. L. Butler-Purry. Multi-agent technology for self-healing shipboard power systems [C]. Proceedings of the 13th International Conference on Intelligent Systems Application to Power Systems,2005:207-211.
[138]崔金兰,刘天琪,李兴源.含有分布式发电的配电网重构研究[J].电力系统保护与控制,2008,36(15)：37-40.
[139] Z. M. Yasin, T. K. A. Rahman, F. K. Elektrik. Service Restoration in Distribution Network with Distributed Generation [C]. The 4th Student Conference on Research and Development (SCOReD 2006), Shah Alam, Selangor, MALAYSIA,27-28 June, 2006:200-206.
[140] Joon-Ho Choi, Jae-Chul Kim, Seung-Ⅱ Moon. Integration Operation of Dispersed
Generations to Automated Distribution Networks for Network Reconfiguration [C]. KEEE International Transactions on Power Engineering,2002,12(3):102-108.
[141]王守相,李晓静,肖朝霞等.含分布式电源的配电网供电恢复的多代理方法[J].电力系统自动化,2007,31(10)：61-65.
[142] S. Talukdar, V. C. Ramesh. A Multi-agent Technique for Contingency Constrained Optimal Power Flows [J]. IEEE Transaction on Power Systems,1994,9(2):855-861.
[143] T. Nagata, H. Nakayama, M. Utatani, et al. A multi-agent approach to Power system normal state operations [C]. IEEE PES Summer Meeting Proeeedings,2002: 1582-1586.
[144]盛戈嗥,涂光瑜,罗毅,等.基于多Agent的二级电压控制系统[J].电力系统自动化,2002,26(5)：20-25.
[145]曹立霞,厉吉文,程新功,等.基于多Agent技术的分布式电压无功优化控制系统[J].电网技术,2004,28(7)：30-33.
[146]刘志宏,吴福保,范敏等.基于多Agent的配电网电压无功优化控制及其应用[J].电力系统及其自动化,2003,27(16)：74-77.
[147] Z. Li, Y. Liu. Reactive Power Optimization Using Agent-Based Grid Computing [C]. the 7th International Power Engineering Conference,2005.
[148] B. Zhao, C X. Guo, Y. J. Cao. A Multiagent-Based Particle Swarm Optimization Approach for Optimal Reactive Power Dispatch [J]. IEEE Transactions on Power Systems,2005,20(2):1070-1078.
[149] A. L. Dimeas, N. D. Hatziargyriou. Operation of A Multiagent System for Microgrid Control [J]. IEEE Transactions on Power Systems,2005,20(3):1447-1455.
[150]李晓露,石东源,丁振华等.EMS的MAS体系结构研究[J].电力系统自动化,2001,25(11)：36-4.
[151] A. Al-Hinai, A. Feliachi. Application of Intelligent Control Agents in Power Systems with Distributed Generators [C]. Proceedings of IEEE PES Power Systems Conference and Exposition,2004,3:1514-1519.
[152] P. Wei, Y. Yan, Y. Ni, J. Yen, F. F. Wu. A Decentralized Approach for Optimal Wholesale Cross-Border Trade Planning Using Multi-Agent Technology [J]. IEEE Transactions on Power Systems,2001,16(4):833-838.
[153] J. Yu, J. Z. Zhou, J. J. Yang, and et al. Agent-Based Retail Electricity Market: Modeling and Analysis [C]. Proceedings of 2004 International Conference on Machine Learning and Cybernetics,2004:95-100.
[154]韩水,汪定伟.基于多代理技术的购电—输电计划优化方法[J].电力系统自动化,2002,26(13)：43-45.
[155] H. Wan, K. K. Li, K. P. Wong. Multi-Agent Application of Substation Protection Coordination with Distributed Generators [C]. Proceedings of International Conference on Future Power Systems,2005.
[156] X. Zeng, K. K. Li, W. L. Chan, S. Su. Multi-agent Based Protection for Distributed Generation Systems [C]. IEEE International Conference on Electric Utility Deregulation, Restructuring and Power Technologies,2004,1:393-397.
[157] J. S. Heo and K. Y. Lee. A Multi-Agent System-Based Intelligent Identification System for Power Plant Control and Fault-Diagnosis [C]. IEEE Congress on Evolutionary Computation,2006:1544-1551.
[158] B. Enacheanu, A. Martin, Ch. Andrieu, et al. Future Distribution Network Architectures:Approach with a CRISP experimentation [C]. International Conference on Future Power Systems,2005:1-6.
[159] Chen-Ching Liu, Juhwan Jung, G. T. Heydt, et al. The strategic power infrastructure defense (SPID) system:a conceptual design [J]. IEEE Control Systems Magazine, 2000,20(4):40-52.
[160] G. T. Heydt, C. C. Liu, A. G. Phadke, et al. Solution for the crisis in electric power supply [J]. IEEE Computer Applications in Power,2001,14(3):22-30.
[161] P. J. Modi, W. M. Shen, M. Tambe, and M. Yokoo. An Asynchronous Complete Method for Distributed Constraint Optimization [C]. Proceedings of Autonomous
Agents and Multi-agent Systems,2003.
[162] T. Nagata, H. Watanabe, M. Ohno, H. Sasaki. A multi-agent approach to power system restoration [C]. International Conference on Power System Technology, 2000,3:1551-1556.
[163] L. Sun, D. A. Cartes. Reconfiguration of shipboard radial power system using intelligent agents [C]. Proceedings of Electrical Machine Technology Symposium, 2004.
[164] T. Nagata, H. Fujita, H. Sasaki. Decentralized Approach to Normal Operations for Power System Network [C]. Proceedings of the 13th International Conference on Intelligent Systems Application to Power Systems,2005.
[165] F. Bellifemine, G. Caire, T. Trucco, et al. JADE administrator's guide [EB/OL]. (2007-06-18) [2008-07-30]. http://jade.tilab.com.
[166] S. D. J. McArthur, E. M. Davidson, V. M. Catterson, et al. Multi-Agent systems for power engineering applications, part I:concepts, approaches, and technical challenges [J]. IEEE Transactions on Power Systems,2007,22(4):1743-1752.
[167] S. D. J. McArthur, E. M. Davidson, V. M. Catterson, et al. Multi-Agent systems for power engineering applications, part II:technologies, standards, and tools for building multi-agent systems [J]. IEEE Transactions on Power Systems,2007,22(4): 1753-1759.
[168] S. K. Srivastava, H. Xiao, K. L. Butler. Multi-Agent system for automated service restoration of shipboard power systems [C]. Proceedings of 15th International Conference on Computer Applications in Industry Engineering. San Diego, American,2002.
[169] W. Isamu, N. Makoto. A genetic algorithm for optimizing switching sequence of service restoration in distribution systems [C]. Proceedings of the 2004 Congress on Evolutionary Computation. America:IEEE,2004:1683-1690.
[170] C. C. Liu, S. J. Lee, S. S. Venkata. An expert system operational aid for restoration
and loss reduction of distribution systems [J]. IEEE Transactions on Power Systems, 1988,3(2):619-626.
[171] K. Simakura, J. Inagaki, Y. Matsunoki, et al. A knowledge-based method for making restoration plan of bulk power system [J]. IEEE Transactions on Power Systems, 1992,7(2):914-920.
[172] J. Kodama, T. Hamagami, H. Shinji, et al. Multi-agent-based autonomous power distribution network restoration using contract net protocol [J]. Electrical Engineering in Japan,2009,166(4):56-63.
[173] S. Moheuddin, A. Noore, M. Choudhry. A reconfigurable distributed multiagent system optimized for scalability [J]. International Journal of Computational Intelligence,2009,5(1); 60-71.
[174]王增平,张丽,徐玉琴,等.含分布式电源的配电网大面积断电供电恢复策略[J].中国电机工程学报,2010,30(34)：8-14.
[175]刘健,徐精求,程红丽.紧急状态下配电网大面积断电快速恢复算法[J].中国电机工程学报,2004,24(12)：132-138.
[2]焦寨军,沈兵,李红江.几种遗传算法在舰船电力系统网络重构中应用及比较[J].微计算机信息,2005,21(34)：184-187.
[3] K. L. Bulter. An ONR young investigator project-predietive reconfiguration of shipboard powers ystems [C]. IEEE Power Engineering Society General Meeting, 2003,1:106-107.
[4]杨秀霞,张晓锋,张毅.大型舰船电力系统网络重构研究[J].海军工程大学学报,2004,16(2)：44-47.
[5] EPRI US, EDF R&D. Profiling and Mapping of Intelligent Grid R&D Programs [R]. EPRI, Palo Alto, CA, USA and EDF R&D, Clamart, France:2006.
[6] European Commission. European Technology Platform Smart Grids:Vision and Strategy for Europe's Electricity Networks of the Future [R/OL]. Luxembourg:Office for Official Publications of the European Commission,2006 [2009-12-18]. http://ec.europa.eu/research/energy/pdf/smartgrids_en.pdf.
[7] Commission of the European Communities. Green Paper:A Europearl Strategy for Sustainable, Competitive and Secure Energy [R]. Brussels, Belgium:Communities, Commission of the European,2006.
[8]余贻鑫,栾文鹏.智能电网[J].电网与清洁能源,2009,25(1)：1-5.
[9]刘振亚.智能电网技术[M].北京：中国电力出版社,2010.
[10]王成山,王守相,郭力.我国智能配电技术展望[J].南方电网技术.2010,4(1)：18-22.
[11]战杰,肖静,赵义术.分布式电源和微网在智能配电网自愈功能中的作用分析[J].山东电力高等专科学校学报.2010,13(2)：33-36.
[12]黄盛.智能配电网通信业务需求分析及技术方案[J].电力系统通信,2010,31(12)：10-12,17.
[13]陆一鸣,刘东,柳劲松,等.智能配电网信息集成需求及模型分析[J].电力系统自动化,2010,34(8)：1-4,96.
[14]贾东梨,孟晓丽,宋晓辉.智能配电网自愈控制技术体系框架研究[J].电网与清洁能源,2011,27(2)：14-18.
[15]焦彦军,苑峰,苑玉山.“自愈”性配电网自动化系统建设研究[C].中国高等学校电力系统及其自动化专业第二十五届学术年会,2009.
[16] T. Nagata, H. Sasaki, R. Yokoyama. Power system restoration by joint usage of expert system and mathematical programming approach [J]. IEEE Transactions on Power Systems,1995,10(3):1473-1479.
[17] N. D. R. Sarma, V. C. Prasad, K. S. Prakasa Rao, V. Sankar. A new network reconfiguration technique for service restoration in distribution networks [J]. IEEE Transactions on Power Delivery,1994,9(4):1936-1942.
[18]张玉眷,杨成峰,彭亚楠,等.配电网非故障区恢复供电方法研究[J].供用电,2007,24(5)：22-24.
[19]李海锋,张尧,钱国基,等.配电网故障恢复重构算法研究[J].电力系统自动化,2001,25(8)：22-24.
[20]郑俊健.配电网故障恢复方法研究[J].科技资讯,2010,(21)：139-140.
[21]张玉春,杨成峰,彭亚楠,等.配电网故障恢复的方法[J].中国设备工程,2008,(4)：49-51.
[22] H. H. Zeineldin, K. Bhattacharya, E. F. El-saadany, et al. Impact of intentional islanding of distributed generation on electricity market prices [J]. IEE Proceedings of Generation, Transmission and Distribution,2006,153(2):147-154.
[23]卢志刚,董玉香.含分布式电源的配电网故障恢复策略[J].电力系统自动化,2007,31(1)：89-92.
[24]易新,陆于平.分布式发电条件下的配电网孤岛划分算法[J].电网技术,2006,
30(7)：50-54.
[25]尹丽燕,于继来.多时间段落的配电网络动态重构[J].中国电机工程学报,2002,22(7)：44-48,80.
[26]刘扬,杨建军,魏立新.改进遗传模拟退火算法在配电网络重构中的应用[J].电力系统及其自动化学报,2004,16(5)：39-42,74.
[27]金丽成,邱家驹.基于CMAC神经网络的配网重构模型[J].浙江大学学报,2004,38(6)：784-788.
[28]韩学军,陈鹏,国新凤,等.基于潮流计算的配电网重构方法[J].电网技术,2007,31(17)：60-63.
[29]居荣,唐小波,鞠勇,等.用于减小供电成本的配电网络重构[J].电气应用,2007,26(1)：42-44,64.
[30]魏智博,刘艳,顾雪平.基于DPSO算法以负载恢复为目标的网络重构[J].电力系统及其自动化学报,2007,31(1)：38-42.
[31]叶远波.故障后配网系统网络重构的研究[J].华东电力,2002,(9)：60-64.
[32]张玉春,杨成峰,曹海英,等.配电网络故障恢复重构的改进遗传算法[J].华中电力,2007,20(4)：18-22.
[33]回志澎,冀路明,陈新刚,等.现代舰船区域配电[J].船舶工程,2005,27(6)：63-67.
[34] R. W. Ashton, J. G. Ciezki. A Novel Power Systems Program at the Naval Post graduate School [J]. IEEE Transactions on Power Systems,1997,12(2):515-520.
[35]陈虹.基于直流配电系统的船舶综合电力系统[J].舰船科学技术,2005,27(增)：31-37.
[36]高磊,吴学智.舰船D-ZED环境PLC信号衰减分析[J].舰船电子工程,2007,27(4)：145-148.
[37]王征,王家林,姚刚等.基于多Agent的船舶电力系统故障诊断系统设计[J].船电技术,2010,30(5)：1-6.
[38]张毅,杨秀霞.舰船电力系统网络重构研究综述[J].电工技术学报,2005,20(8)：
1-6.
[39] K. L. Bulter, N. D. R. Sarma, C. Whitcomb, et al. Shipboard systems deploy automated protection [J]. IEEE Computer Applications in Power,1998,11(2):31-36.
[40]吕昊,叶志浩,纪锋,等.开关动作次数最少目标函数的舰船电力系统重构[J].中国修船,2009,22(1)：26-29.
[41]刘维亭,邱赞.网络重构法在舰船区域配电系统中的应用研究[J].舰船科学技术,2009,31(2)：53-57.
[42]王文明,刘维亭,朱志字,等.基于图论理论的舰船配电网故障恢复算法[J].船海工程,2008,37(5)：86-89,94.
[43] S. Srivastava, K. L. Butler-Purry. Expert-system Method for Automatic Reconfigura-tion for Restoration of Shipboard Power System [J]. IEE Proceedings Generation, Transmission and Distribution,2006,153(3):253-260.
[44] S. K. Srivastava, K. L. Butler-Purry, N. D. R. Sarma. Shipboard Power Restored for Aetive Duty [J]. IEEE Computer Applications in Power.2002,15(3):16-23.
[45] Zhiping Ding, Srivastava. S, Cartes. D. Expert System based Dynamic Load Shedding Scheme for Shipboard Power Systems [C]. In:41st IAS Annual Conference Record of the 2006. Oct.2006:1338-1344.
[46] K. L. Butler, N. D. R. Sarma. Intelligent Network Reconfiguration of Shipboard Power Systems [C]. IEEE Power Engineering Society General Meeting.2003,4: 2435-2439.
[47] Fan Ji-Yuan, Zhang Lan, J. D. McDonald. Distribution Network Reconfiguration: Single Loop Optimization [J]. IEEE Transactions on Power Systems,1996,11 (3): 1643-1647.
[48] N. D. R. Sarma, K. S. Prakasa Rao. A New 0-1 Integer Programming Method of Feeder Reconfiguration for Loss Minimization in Distribution Systems [J]. Electric Power System Research,1995,33(2):125-131.
[49] A. Abur. Modified linear programming method for distribution system reconfigure-
ation[J]. International Journal of Electrical Power and Energy System,1996,18(7): 469-474.
[50] T. P. Wagner, A. Y. Chikhani, R. Hackam. Feeder reconfiguration for loss reduction: An application of distribution automation [J]. IEEE Transactions on Power Delivery, 1991,6(4):1922-1933.
[51] K. Aoki, T. Ichimori, M. Kanezashi. Normal State Optimal Load Allocation in Distribution Systems [J]. IEEE Transactions on Power Delivery,1987,2(1): 147-155.
[52] K. L. Butler, N. D. R. Sarma, V. R. Prasad. A New Method of Network Reconfiguration for Service Restoration in Shipboard Power Systems [C]. IEEE Transmission and Distribution Conference.1999,2:658-662.
[53] K. L. Butler, N. D. R. Sarma, V. R. Prasad. Network reconfiguration for service restoration in shipboard power distribution systems [J]. IEEE Transactions on Power System,2001,16(4):653-661.
[54] K. L. Butler, N. D. R. Sarma. Self-Healing Reconfiguration for Restoration of Naval Shipboard Power Systems [J]. IEEE Transactions on Power Systems,2004, 19(2):754-762.
[55] K. Nara, A. Shiose, M. Kitagawa. Implementation of Genetic Algorithm for Distribution Systems Loss Minimum Reconfiguration [J]. IEEE Transactions on Power Systems,1992,7(3):1044-1051.
[56] W. P. Luan, M. R. Irving, J. S. Daniel. Genetic Algorithm for Supply Restoration and Optimal Load Shedding in Power System Distribution Networks [J]. IEE Proc-Gener, Transmand Distrib,2002,149(2):145-151.
[57]刘莉,陈学允.基于模糊遗传算法的配电网络重构[J].中国电机工程学报,2000,20(2)：66-69.
[58]李晓明,黄彦浩,尹项根.基于改良策略的配电网重构遗传算法[J].中国电机工程学报,2004,24(2)：49-54.
[59]毕鹏翔,刘健,等.配电网络重构的改进遗传算法[J].电力系统自动化,2001,25(9)：53-55.
[60]盛四清,梁志瑞,等.基于遗传算法的地区电网停电恢复[J].电力系统自动化,2002,26(2)：57-61.
[61]余贻鑫,丘炜,刘若沁.基于启发式算法与遗传算法的配电网重构[J].电网技术,2001,25(11)：19-22.
[62]余贻鑫,段刚.基于最短路算法和遗传算法的配电网络重构[J].中国电机工程学报,2000,20(9)：44-49.
[63]杨秀霞,张晓锋,张毅,等.基于启发式遗传算法的舰船电力系统网络重构研究[J].中国电机工程学报,2003,23(10)：42-46.
[64]杨秀霞,张晓锋,张毅,等.免疫遗传算法在舰船电力系统供电恢复中的应用研究[J].中国电机工程学报,2004,24(9)：80-86.
[65]杨秀霞,张晓锋,张毅,等.基于加速遗传算法的舰船电力系统故障恢复[J].电工技术学报,2005,20(5)：53-57.
[66]何芳,蔡兴国.基于改进遗传算法的舰船电力系统网络重构[J].电工技术学报,2006,21(9)：25-30.
[67]庄肖波,孟思齐,刘维亭.基于混沌遗传算法的舰船电力系统故障恢复[J].继电器,2007,35(21)：39-42.
[68]何祖军,王文明,刘维亭.基于混沌遗传算法的舰船区域配电系统故障恢复算法[J].船电技术,2008,28(6)：380-382.
[69]王敏,刘维亭.混沌遗传算法在船舶电力系统供电恢复中的应用研究[J].江苏科技大学学报,2008,22(5)：6-10.
[70]刘大宝,夏立,王征.多智能体遗传算法在船舶电力网络重构中的应用[J].中国航海,2011,34(4)：39-44,66.
[71]黄席樾,向长城,殷礼胜.现代智能算法理论及应用[M].北京：科学出版社,2005.
[72]靳现林,王建生,韩蕾.一种改进粒子群优化算法的配电网重构[J].东北电力
技术,2007,(10)：11-15.
[73]许立雄,吕林,刘俊勇.基于改进粒子群优化算法的配电网络重构[J].电力系统自动化,2006,30(7)：27-30,79.
[74]卢志刚,杨国良,张晓辉,文莹.改进二进制粒子群优化算法在配电网络重构中的应用[J].电力系统保护与控制,2009,37(7)：30-34.
[75]靳晓凌,赵建国.基于改进二进制粒子群优化算法的负载均衡化配电网重构[J].电网技术,2005,29(23)：40-43.
[76]李振坤,陈星莺,余昆,等.配电网重构的混合粒子群算法[J].中国电机工程学报,2008,28(31)：35-41.
[77]吕林,王佳佳,刘俊勇,等.基于多粒子群分层分布式优化的配电网重构[J].电力系统保护与控制,2009,37(19)：56-60,68.
[78]刘自发,葛少云,余贻鑫.一种混合智能算法在配电网络重构中的应用[J].中国电机工程学报,2005,25(15)：73-78.
[79]白丹丹,刘观起,郭丽.基于改进粒子群算法的配电网重构的研究[J].华北电力大学学报,2006,33(6)：20-23.
[80]肖鲲,黄挚雄.多智能体粒子群算法在配电网络重构中的应用[J].计算机工程与应用,2010,46(8)：221-224,227.
[81]李军军,王锡淮,肖建梅.基于离散微粒群优化算法的舰船电力系统网络重构[J].中国电机工程学报,2006,26(25)：6-10.
[82]王锡淮,李军军,肖建梅.基于梯度DPSO算法在舰船电力系统网络重构[J].电工技术学报,2007,22(12)：140-145.
[83]王锡淮,李军军,肖建梅.求解舰船电力系统网络重构的贪婪DPSO算法[J].控制与决策,2008,23(2)：157-161.
[84]陈雁,孙海顺,文劲宇,等.改进粒子群算法在船舶电力系统网络重构中的应用[J].电力自动化设备,2011,31(3)：29-34,39.
[85]刘大宝,夏立,王征.多Agent粒子群算法在船舶电力网络重构中的应用[J].船电技术,2011,31(11)：42-47.
[86]李军军,许波桅,甘世红,等.基于贪婪度表的DPSO求解舰船电力系统网络重构[J].电工技术学报,2011,26(5)：146-151.
[87]蔡自兴,徐光祜.人工智能及其应用[M].北京：清华大学出版社,2010.
[88]陈根军,王磊,唐国庆.基于蚁群最优的配电网络重构算法[J].电力系统及其自动化学报,2001,13(2)：48-53.
[89]甘学涛,宋喜,王志刚,等.基于蚁群算法的配电网络重构模型及其应用[J].西北农林科技大学学报,2005,33(5)：157-160.
[90]汪超,马红卫,胡志坚,等.基于蚁群系统(ACS)的配电网重构[J].继电器,2006,34(23)：35-38,43.
[91]徐延炜,贾嵘.基于人工免疫思想的蚁群算法(AIACS)在配电网重构中的[J].电力系统保护与控,2010,38(18)：89-93
[92]黄健,张尧,李绮雯.蚁群算法在配电网重构的应用[J].电力系统及其自动化学报,2007,19(4)：59-64.
[93]李哲,夏立.改进蚁群算法求解船舶电力系统故障重构问题[J].电力系统及其自动化学报,2009,21(2)：47-52.
[94]王征,王永骥,李哲.基于改进蚁群算法的船舶电力系统故障重构研究[J].计算技术与自动化,2010,29(1)：1-4.
[95] L. N. de Castro, F. J. Von Zuben. Learning and optimization using the clonal selection principle [J]. IEEE Transactions on Evolutionary Computation,2002,6(3): 239-251.
[96]王击,罗安,张敏,等.修正克隆遗传算法在配电网络重构中的应用[J].湘潭矿业学院学报,2004,19(1)：80-83.
[97]何友林,张洪涛,郭创新,等.抗体克隆算法在配电网络重构中的应用[J].继电器,2006,34(16)：22-26,43.
[98]周辉,王击,罗安,等.克隆遗传算法与模拟退火算法相结合的配电网络重构[J].继电器,2007,35(7)：41-45.
[99]邹凤娇,王击,徐留杰.基于免疫克隆遗传算法的配电网络重构[J].微计算机
信息,2009,25(7)：222-224.
[100]张利民,马强,李振坤,等.基于禁忌克隆遗传算法的配电网故障恢复重构[J].电力系统及其自动化学报,2010,22(1)：60-64.
[101]谢林峰,姚强.基于自适应免疫克隆选择算法的配电网重构[J].南方电网技术,2011,5(6)：81-85.
[102]朱志宇,刘维亭,庄肖波.基于克隆算法的舰船电力系统故障恢复[J].电工技术学报,2009,12(1)：155-170.
[103]黄巧亮,王文明,刘维亭,等.基于克隆算法的舰船区域配电系统故障恢复算法[J].舰船科学技术,2009,31(11)：97-101.
[104]王敏,刘维亭.免疫克隆选择算法在船舶电力系统故障恢复中的应用研究[J].电力系统保护与控制,2009,37(1)：19-23,60.
[105] Chiang Hsiao-Dong, Jean-Jumeau, Rene. Optimal Network Reconfigurations in Distribution Systems:Part 1:A New Formulation and a Solution Methodology [J]. IEEE Transactions on Power Delivery,1990,5(4):1902-1909.
[106] Wang Jin-Cheng, Chiang Hsiao-Dong, G. R. Daring. An Efficient Algorithm for Real-time Network Reconfiguration in Large Scale Unbalanced Distribution Systems [J]. IEEE Transactions on Power Systems,1996,11(1):511-517.
[107] Jeon Young-Jae, Kim Jae-Chul, Kim Jin-O, et al. An Efficient Simulated Annealing Algorithm for Network Reconfiguration in Large-scale Distribution Systems [J]. IEEE Transactions on Power Delivery,2002,17(4):1070-1078.
[108] Brown R. E. Distribution Reliability Assessment and Reconfiguration Optimization [C]. Proceedings of the IEEE Power Engineering Society Transmission and Distribution Conference,2001,2:994-999.
[109]胡敏羞,陈元.配电系统最优网络重构的模拟退火算法[J].电力系统自动化,1994,18(2)：24-28.
[110]陈根军,李线洗,唐国庆.基于Tabu搜索的配电网络重构算法[J].中国电机工程学报,2002,22(10)：28-33.
[111]左飞,周家启.TS算法在配电网络重构中的应用[J].电力系统自动化学报,2004,16(1)：66-69.
[112]葛少云,刘自发,余贻鑫.基于改进禁忌搜索的配电网重构[J].电网技术,2004,28(23)：22-26.
[113]张栋,张刘春,傅正财.基于改进禁忌算法的配电网络重构[J].电工技术学报,2005,20(11)：60-64.
[114]张忠会,李曼丽,熊宁,等.基于改进禁忌搜索的配电网重构[J].继电器,2007,35(10)：4144.
[115]熊宁,程浩忠.基于开关组的禁忌算法在配电网动态重构中的应用[J].电力系统自动化,2008,32(11)：56-60.
[116]王林川,梁栋,于冬皓,等.基于遗传和禁忌搜索混合算法的配电网重构[J].电力系统保护与控制,2009,37(6)：27-31.
[117]王林川,李漫,张木子,等.基于蚁群禁忌搜索混合算法的配电网重构[J].吉林电力,2010,38(5)：34-36.
[118] H. Kim, Y. Ko, K. H. Jung. Artificial Neural-Network Based Feeder Reconfiguration for Loss Reduction in Distribution Systems [J]. IEEE Transactions on Power Delivery,1993,8(3):1356-1366.
[119] M. A. Kashem, G. B. Jasmon, A. Mohamed, et al. Artificial Neural Network Approach to Network Reconfiguration for Loss Minimization in Distribution Networks [J]. International Journal of Electrical Power and Energy System,1998, 20(4):247-258.
[120] K. L. Bulter, N. D. R. Sarma. General Reconfiguration Methodology for AC Radial Shipboard Power Systems [C]. IEEE 2000 Power Engineering Society Winter Meeting.2000,2:1226-1230.
[121] J. A. Momoh, J. Z. Zhu, S. S. Kaddah. Optimal Load Shedding Study of Naval-ship Power System Using the Everett Optimization Technique [J]. Electric Power Systems Research,2002,60(3):145-152.
[122] S. K. Srivastava, K. L. Butler-Purry. A Pre-hit Probabilistic reconfiguration methodology for shipboard Power systems [C]. IEEE Electric Ship Technologies Symposium,2005:99-104.
[123] S. K. Srivastava, K. L. Butler-Purry. A Probability Based Predictive Reconfiguration Method for Shipboard Power Systems [C]. IEEE Probabilistic Methods Applied to Power Systems International Conference,2004:813-818.
[124] K. L. Butler, N. D. R. Sarma. Preventive self-healing shipboard power distribution systems [C]. IEEE Power Engineering Society General Meeting,2005,3: 2443-2444.
[125] S. K. Srivastava, H. Xiao, K. L. Butler-Purry. Multi-agent system for automated service restoration of shipboard power systems [J]. Journal of Computer Information Systems,2003,44(1):119-123.
[126] L. Sun, D. Cartes. A multi-Agent system for reconfiguration of shipboard power systems [J]. Transactions on International Association of Mechanical Engineers, 2004,1 (3):425-431.
[127] A. Feliachi, K. Schoder, S. Ganesh, H. J. Lai. Distributed Control Agent Approach to Energy Management in Electric Shipboard Power System [C]. IEEE Power Engineering Society General Meeting,2006.
[128] J. M. Solanki, N. N. Schulz, W. Gao. Reconfiguration for Restoration of Power Systems Using a Multi-agent System [C]. Proceedings of the 37th Annual North American Power Symposium,2005:390-395.
[129] J. A. Momoh, O. S. Diouf. Optimal Reconfiguration of the Navy Ship Power System Using Agents [C]. Proceedings of the IEEE Power Engineering Society Transmission and Distribution Conference,2006:562-567.
[130] G. Morejon, S. K. Srivastava, D. A. Cartes. Integration Virtual Test Bed and JADE Agent Platform Using CORBA for Reconfiguration of Shipboard Power Systems [C]. IEEE Power Engineering Society General Meeting,2006:18-22.
[131] J. M. Solanki, N. N. Schulz. Using intelligent multi-agent systems for shipboard power systems reconfiguration [C]. in Proceedings of the 13th International Conference on Intelligent Systems Application to Power Systems,2005:212-214.
[132] Huang Kai, S. K. Srivastava, D. A. Cartes, et al. Intelligent Agents applied to reconfiguration of mesh structured power systems [C]. International Conference on Intelligent Systems Applications to Power Systems (ISAP), Kaohsiung, Taiwan, China,2007.
[133] Huang Kai. Shipboard power system reconfiguration using multi-agent system [D]. Florida:The Florida State University,2007.
[134] J. M. Solanki, S. Khushalani, N. N. Schulz. A multi-agent solution to distribution systems restoration [J]. IEEE Transactions on Power Systems,2007,22(3): 1026-1034.
[135] T. Nagata, H. Sasaki. A multi-agent approach to power system restoration [J]. IEEE Transactions on Power Systems,2002,17(2):457-462.
[136] J. A. Momoh. Navy ship power system restoration using multi-agent approach [C]. IEEE Power Engineering Society General Meeting, Montreal, Quebec, Canada, 2006:14-18.
[137] K. L. Butler-Purry. Multi-agent technology for self-healing shipboard power systems [C]. Proceedings of the 13th International Conference on Intelligent Systems Application to Power Systems,2005:207-211.
[138]崔金兰,刘天琪,李兴源.含有分布式发电的配电网重构研究[J].电力系统保护与控制,2008,36(15)：37-40.
[139] Z. M. Yasin, T. K. A. Rahman, F. K. Elektrik. Service Restoration in Distribution Network with Distributed Generation [C]. The 4th Student Conference on Research and Development (SCOReD 2006), Shah Alam, Selangor, MALAYSIA,27-28 June, 2006:200-206.
[140] Joon-Ho Choi, Jae-Chul Kim, Seung-Ⅱ Moon. Integration Operation of Dispersed
Generations to Automated Distribution Networks for Network Reconfiguration [C]. KEEE International Transactions on Power Engineering,2002,12(3):102-108.
[141]王守相,李晓静,肖朝霞等.含分布式电源的配电网供电恢复的多代理方法[J].电力系统自动化,2007,31(10)：61-65.
[142] S. Talukdar, V. C. Ramesh. A Multi-agent Technique for Contingency Constrained Optimal Power Flows [J]. IEEE Transaction on Power Systems,1994,9(2):855-861.
[143] T. Nagata, H. Nakayama, M. Utatani, et al. A multi-agent approach to Power system normal state operations [C]. IEEE PES Summer Meeting Proeeedings,2002: 1582-1586.
[144]盛戈嗥,涂光瑜,罗毅,等.基于多Agent的二级电压控制系统[J].电力系统自动化,2002,26(5)：20-25.
[145]曹立霞,厉吉文,程新功,等.基于多Agent技术的分布式电压无功优化控制系统[J].电网技术,2004,28(7)：30-33.
[146]刘志宏,吴福保,范敏等.基于多Agent的配电网电压无功优化控制及其应用[J].电力系统及其自动化,2003,27(16)：74-77.
[147] Z. Li, Y. Liu. Reactive Power Optimization Using Agent-Based Grid Computing [C]. the 7th International Power Engineering Conference,2005.
[148] B. Zhao, C X. Guo, Y. J. Cao. A Multiagent-Based Particle Swarm Optimization Approach for Optimal Reactive Power Dispatch [J]. IEEE Transactions on Power Systems,2005,20(2):1070-1078.
[149] A. L. Dimeas, N. D. Hatziargyriou. Operation of A Multiagent System for Microgrid Control [J]. IEEE Transactions on Power Systems,2005,20(3):1447-1455.
[150]李晓露,石东源,丁振华等.EMS的MAS体系结构研究[J].电力系统自动化,2001,25(11)：36-4.
[151] A. Al-Hinai, A. Feliachi. Application of Intelligent Control Agents in Power Systems with Distributed Generators [C]. Proceedings of IEEE PES Power Systems Conference and Exposition,2004,3:1514-1519.
[152] P. Wei, Y. Yan, Y. Ni, J. Yen, F. F. Wu. A Decentralized Approach for Optimal Wholesale Cross-Border Trade Planning Using Multi-Agent Technology [J]. IEEE Transactions on Power Systems,2001,16(4):833-838.
[153] J. Yu, J. Z. Zhou, J. J. Yang, and et al. Agent-Based Retail Electricity Market: Modeling and Analysis [C]. Proceedings of 2004 International Conference on Machine Learning and Cybernetics,2004:95-100.
[154]韩水,汪定伟.基于多代理技术的购电—输电计划优化方法[J].电力系统自动化,2002,26(13)：43-45.
[155] H. Wan, K. K. Li, K. P. Wong. Multi-Agent Application of Substation Protection Coordination with Distributed Generators [C]. Proceedings of International Conference on Future Power Systems,2005.
[156] X. Zeng, K. K. Li, W. L. Chan, S. Su. Multi-agent Based Protection for Distributed Generation Systems [C]. IEEE International Conference on Electric Utility Deregulation, Restructuring and Power Technologies,2004,1:393-397.
[157] J. S. Heo and K. Y. Lee. A Multi-Agent System-Based Intelligent Identification System for Power Plant Control and Fault-Diagnosis [C]. IEEE Congress on Evolutionary Computation,2006:1544-1551.
[158] B. Enacheanu, A. Martin, Ch. Andrieu, et al. Future Distribution Network Architectures:Approach with a CRISP experimentation [C]. International Conference on Future Power Systems,2005:1-6.
[159] Chen-Ching Liu, Juhwan Jung, G. T. Heydt, et al. The strategic power infrastructure defense (SPID) system:a conceptual design [J]. IEEE Control Systems Magazine, 2000,20(4):40-52.
[160] G. T. Heydt, C. C. Liu, A. G. Phadke, et al. Solution for the crisis in electric power supply [J]. IEEE Computer Applications in Power,2001,14(3):22-30.
[161] P. J. Modi, W. M. Shen, M. Tambe, and M. Yokoo. An Asynchronous Complete Method for Distributed Constraint Optimization [C]. Proceedings of Autonomous
Agents and Multi-agent Systems,2003.
[162] T. Nagata, H. Watanabe, M. Ohno, H. Sasaki. A multi-agent approach to power system restoration [C]. International Conference on Power System Technology, 2000,3:1551-1556.
[163] L. Sun, D. A. Cartes. Reconfiguration of shipboard radial power system using intelligent agents [C]. Proceedings of Electrical Machine Technology Symposium, 2004.
[164] T. Nagata, H. Fujita, H. Sasaki. Decentralized Approach to Normal Operations for Power System Network [C]. Proceedings of the 13th International Conference on Intelligent Systems Application to Power Systems,2005.
[165] F. Bellifemine, G. Caire, T. Trucco, et al. JADE administrator's guide [EB/OL]. (2007-06-18) [2008-07-30]. http://jade.tilab.com.
[166] S. D. J. McArthur, E. M. Davidson, V. M. Catterson, et al. Multi-Agent systems for power engineering applications, part I:concepts, approaches, and technical challenges [J]. IEEE Transactions on Power Systems,2007,22(4):1743-1752.
[167] S. D. J. McArthur, E. M. Davidson, V. M. Catterson, et al. Multi-Agent systems for power engineering applications, part II:technologies, standards, and tools for building multi-agent systems [J]. IEEE Transactions on Power Systems,2007,22(4): 1753-1759.
[168] S. K. Srivastava, H. Xiao, K. L. Butler. Multi-Agent system for automated service restoration of shipboard power systems [C]. Proceedings of 15th International Conference on Computer Applications in Industry Engineering. San Diego, American,2002.
[169] W. Isamu, N. Makoto. A genetic algorithm for optimizing switching sequence of service restoration in distribution systems [C]. Proceedings of the 2004 Congress on Evolutionary Computation. America:IEEE,2004:1683-1690.
[170] C. C. Liu, S. J. Lee, S. S. Venkata. An expert system operational aid for restoration
and loss reduction of distribution systems [J]. IEEE Transactions on Power Systems, 1988,3(2):619-626.
[171] K. Simakura, J. Inagaki, Y. Matsunoki, et al. A knowledge-based method for making restoration plan of bulk power system [J]. IEEE Transactions on Power Systems, 1992,7(2):914-920.
[172] J. Kodama, T. Hamagami, H. Shinji, et al. Multi-agent-based autonomous power distribution network restoration using contract net protocol [J]. Electrical Engineering in Japan,2009,166(4):56-63.
[173] S. Moheuddin, A. Noore, M. Choudhry. A reconfigurable distributed multiagent system optimized for scalability [J]. International Journal of Computational Intelligence,2009,5(1); 60-71.
[174]王增平,张丽,徐玉琴,等.含分布式电源的配电网大面积断电供电恢复策略[J].中国电机工程学报,2010,30(34)：8-14.
[175]刘健,徐精求,程红丽.紧急状态下配电网大面积断电快速恢复算法[J].中国电机工程学报,2004,24(12)：132-138.