电网事故处理智能辅助决策系统的研究
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摘要
电力系统的安全、稳定、经济是电网运行的主要目标。在现代电力系统中,计算机系统提供了报警及故障信息收集功能,这些功能无疑提高了电网运行的系统化水平,并且为获取故障信息提供了技术条件。但另一方面,在紧急以及故障状态下,大量信息的涌入给运行人员准确过滤信息和识别故障增加了难度。随着调度自动化系统性能的不断提高,以及继电保护管理信息系统的推广应用,调度中心所接收到的数据量较以往大量增加。电网发生故障时,调度员往往要面对的是比正常操作时多几倍甚至几十倍的故障相关信息,由于缺乏统一的故障数据综合处理和分析工具,这些大量信息的涌入给调度员事故处理造成很大的不便。为了处理事故,调度员还要迅速检索和查找大量的事故处理相关资料。需要一套有效的事故处理智能决策系统,实现对电网故障的自动快速识别、隔离和恢复。
本文从研究各种电力系统故障诊断理论出发,吸取以往研究成果和不足,提出了在调度自动化系统基础之上实现事故处理智能辅助决策系统的关键技术要点,如智能防误策略、信息流控制等,明确了系统的基本架构和各项功能需求,并研究了事故处置方案生成、智能减载限电、智能转电决策等系统的典型应用的实现方法。该系统在电网正常运行时为调度员提供事故预想及反事故演练的模拟培训平台等功能。电网发生事故时自动提供故障点、故障类型、停电范围、所涉及的重要用户等信息,并根据电网运行方式和网络拓扑信息,智能化或手动生成恢复方案,提供有效的综合防误操作手段,有效保障电网安全稳定运行。
The safety, stability and economic is the main target of the power system operation. In the modern power system, the computer system provides alarm and fault information collection functions, which improves systematic level of the system operation, and provides technological specifications to gain fault information. On the other hand, under the urgent and fault condition, it will be more difficult for operators to filter information and recognize fault when large volume of information pouring in. With the continuous improving of dispatching automatization system performance, and the popularization and application of relay protection management information system, the volume which dispatching centre received has increased more largely than ever before. When there is fault in power grid, it happens frequently that dispatcher needs to face several times or even hundreds of times fault related information than normal operation, also, because of lack of unified integration of data processing and analysis tools , this large pouring information will cause great inconvenience to the dispatcher who deals with the accident. In order to deal with the accident, dispatcher also needs to find and retrieve quickly for lots of relevant accident treatment information. A set of effective fault treatment intelligent decision system is needed to implement automatic rapid identification, isolation and restoration for power grid fault.
This essay analyses various power grid fault diagnosis theory, extracts the previous research findings and deficiency, and suggests some key technology points for implementation of accident treatment intelligent assistant decision-making system based on the dispatch automatic system, such as intelligent preventing misoperation system、information flow control etc, and defines basis structure of the system and various function needs. This system provide dispatcher with accident anticipation and simulated training platform against accidents, and other functions when the power grid is operating normally. When fault happens in the power system, it automatically provide fault point、fault type、power failure area、important users involved and other information, and according to the power system running mode and network topology, it intelligently or manually creates recovery scheme, and provides effective and comprehensive means to prevent the misoperation, which ensures the safety and stability of the power system.
本文从研究各种电力系统故障诊断理论出发,吸取以往研究成果和不足,提出了在调度自动化系统基础之上实现事故处理智能辅助决策系统的关键技术要点,如智能防误策略、信息流控制等,明确了系统的基本架构和各项功能需求,并研究了事故处置方案生成、智能减载限电、智能转电决策等系统的典型应用的实现方法。该系统在电网正常运行时为调度员提供事故预想及反事故演练的模拟培训平台等功能。电网发生事故时自动提供故障点、故障类型、停电范围、所涉及的重要用户等信息,并根据电网运行方式和网络拓扑信息,智能化或手动生成恢复方案,提供有效的综合防误操作手段,有效保障电网安全稳定运行。
The safety, stability and economic is the main target of the power system operation. In the modern power system, the computer system provides alarm and fault information collection functions, which improves systematic level of the system operation, and provides technological specifications to gain fault information. On the other hand, under the urgent and fault condition, it will be more difficult for operators to filter information and recognize fault when large volume of information pouring in. With the continuous improving of dispatching automatization system performance, and the popularization and application of relay protection management information system, the volume which dispatching centre received has increased more largely than ever before. When there is fault in power grid, it happens frequently that dispatcher needs to face several times or even hundreds of times fault related information than normal operation, also, because of lack of unified integration of data processing and analysis tools , this large pouring information will cause great inconvenience to the dispatcher who deals with the accident. In order to deal with the accident, dispatcher also needs to find and retrieve quickly for lots of relevant accident treatment information. A set of effective fault treatment intelligent decision system is needed to implement automatic rapid identification, isolation and restoration for power grid fault.
This essay analyses various power grid fault diagnosis theory, extracts the previous research findings and deficiency, and suggests some key technology points for implementation of accident treatment intelligent assistant decision-making system based on the dispatch automatic system, such as intelligent preventing misoperation system、information flow control etc, and defines basis structure of the system and various function needs. This system provide dispatcher with accident anticipation and simulated training platform against accidents, and other functions when the power grid is operating normally. When fault happens in the power system, it automatically provide fault point、fault type、power failure area、important users involved and other information, and according to the power system running mode and network topology, it intelligently or manually creates recovery scheme, and provides effective and comprehensive means to prevent the misoperation, which ensures the safety and stability of the power system.
引文
[1]刘道兵;顾雪平.地区电网故障恢复的实用化研究[J].电力系统保护与控制, 2010,(021):48~52 .
[2]廖志伟,孙雅明,叶青华.人工智能技术在电力系统故障诊断中应用[J].电力系统及其自动化学报, 2003,(06) :71~79 .
[3]王建元,纪延超,常群,张丽娣. Petri网络理论在电网故障诊断中的应用[J].哈尔滨理工大学学报, 2002,(04) :77~80 .
[4] Hong-Chan Chin. Fault section diagnosis of power system using fuzzy logic .Power Systems,IEEE Transactions on, 2003, 18 (1) :245-250 .
[5] Z. E. Aygen,S. Seker,M. Bagnyamk. Fault section estimation in electrical power systems using artificial neural network approach[J] .Transmission & Distribution Conference 1999. IEEE, 11-16 April 1999, (2) :466-469 .
[6]徐岩.基于广域测量系统的改进电网拓扑结构识别[J].电网技术, 2010,(9) :88-93.
[7]王超.基于着色法网络拓扑分析的电网事故处理辅助决策系统应用[J].电气应用, 2010,(9) :92-95.
[8]李碧君,薛禹胜,顾锦汶.电力系统状态估计问题的研究现状和展望.电力系统自动化.1998,22(11) :53 .
[9]刘辉乐,刘天琪.电力系统动态状态估计的研究现状和展望.电力自动化设备,2004,24(12) :73-77 .
[10] ZENG Qing-feng, ZU Jia-kui, ZHANG Li-tong,. Designing expert system with artificial neural networks.Materials and Design, 2002, 23(3) : 287-290 .
[11] Cho H J, Park J K. An expert system for fault section diagnosis of power systems using fuzzing relations .IEEE Transaction on Power Systems, 1997, 12(1) :342-348 .
[12]李军,阮晓钢.一种基于神经网络的专家系统设计[J].北京工业大学学报, 2003,(02) :171-174.
[13]雷勇.基于神经网络和专家系统的变电站故障诊断和处理系统的构想[J].福建电力与电工, 2003,(04) :21-24.
[14]吴长华,章少华.基于主动式知识库的专家系统建模和推理研究[J].杭州电子工业学院学报, 2001,(01) :30-34.
[15]吴凌云,王华. BP神经网络专家系统在故障诊断中的应用[J].信息技术, 2003, (02):66-68.
[16]朱永利,王艳,耿兰芹,苏丹.基于贝叶斯网络的电网故障诊断[J]电力自动化设备, 2007,(07):33-37 .
[17]刘燕燕.基于模糊神经网络的信息融合在电网故障诊断中的应用[J].继电器, 2005, (09):9-57 .
[18]郭创新,游家训,彭明伟,唐跃中,刘毅,陈济.基于面向元件神经网络与模糊积分融合技术的电网故障智能诊断[J]电工技术学报, 2010,(09):183-190 .
[19]赵爽,任建文.电网故障诊断系统的一种设计与实现[J].华东电力, 2003, (11):19-21.
[20]陈勇.智能技术在电网故障诊断中的应用[J].江苏电机工程, 2007, (04):39-42 .
[21]郭创新,朱传柏,曹一家.电力系统故障诊断的研究现状与发展趋势[J].电力系统自动化, 2006, 30( 8) : 98-103.
[22]梁循.数据挖掘算法与应用[M] .北京:北京大学出版社,2006:20-25.
[23] Rodrigues-Ortiz G, Fernandez-Espinosa V.Data mining techniques to classify energy demand[J].International Journal of Power and Energy System,1999,19(2):168-172.
[24]顾黎强,袁一鸣.数据挖掘技术在电网调度事故决策中的应用[J].供用电.2007,24(5):17-35.
[25]廖志伟,孙雅明.数据挖掘技术及其在电力系统中的应用[J].电力系统自动化.2001,25(11):62-66.
[26]孙卫祥.基于数据挖掘与信息融合的故障诊断方法研究[D]上海交通大学, 2006 .
[27] Lambert-Tones G. Application of Rough Set in Power System Control Center Data Mining[J] .Proceeding of the First International Conference on Machine Learning and Cybernetics. Piscataway. 2002 :627-631 .
[28]聂倩雯;高玮.基于关联规则数据挖掘技术的电网故障诊断[J].电力系统保护与控制.2009,37(9):8-19.
[29]张伯明,陈寿孙.高等电力网络分析[M].北京:清华大学出版社,1996:50-56.
[30]王志鹏.基于信息融合技术的故障诊断方法的研究及应用[D].大连理工大学, 2001 .
[31]刘毅,高振兴,郭创新,彭明伟.一种考虑多层信息融合的电网故障诊断辅助决策方法[J].电力系统保护与控制, 2010,(24) .
[32]赵熙临,周建中,付波,刘辉.基于信息融合技术的电网故障诊断方法[J].华中科技大学学报(自然科学版), 2009, (03):98-101 .
[33]江振华,程时杰.基于开关逻辑的电力系统图形和操作票自动生成系统[J].电力自动化设备,1999,19(3):12-14.
[34]朱奕.基于规则推理的电气防误操作评价系统[J].自动化技术与应用,2000,(2):19.
[35]刘蔚,杨宛辉.操作逻辑函数在操作票专家系统中的应用[J].电力系统及其自动化学报,1999,11(4):39-43
[2]廖志伟,孙雅明,叶青华.人工智能技术在电力系统故障诊断中应用[J].电力系统及其自动化学报, 2003,(06) :71~79 .
[3]王建元,纪延超,常群,张丽娣. Petri网络理论在电网故障诊断中的应用[J].哈尔滨理工大学学报, 2002,(04) :77~80 .
[4] Hong-Chan Chin. Fault section diagnosis of power system using fuzzy logic .Power Systems,IEEE Transactions on, 2003, 18 (1) :245-250 .
[5] Z. E. Aygen,S. Seker,M. Bagnyamk. Fault section estimation in electrical power systems using artificial neural network approach[J] .Transmission & Distribution Conference 1999. IEEE, 11-16 April 1999, (2) :466-469 .
[6]徐岩.基于广域测量系统的改进电网拓扑结构识别[J].电网技术, 2010,(9) :88-93.
[7]王超.基于着色法网络拓扑分析的电网事故处理辅助决策系统应用[J].电气应用, 2010,(9) :92-95.
[8]李碧君,薛禹胜,顾锦汶.电力系统状态估计问题的研究现状和展望.电力系统自动化.1998,22(11) :53 .
[9]刘辉乐,刘天琪.电力系统动态状态估计的研究现状和展望.电力自动化设备,2004,24(12) :73-77 .
[10] ZENG Qing-feng, ZU Jia-kui, ZHANG Li-tong,. Designing expert system with artificial neural networks.Materials and Design, 2002, 23(3) : 287-290 .
[11] Cho H J, Park J K. An expert system for fault section diagnosis of power systems using fuzzing relations .IEEE Transaction on Power Systems, 1997, 12(1) :342-348 .
[12]李军,阮晓钢.一种基于神经网络的专家系统设计[J].北京工业大学学报, 2003,(02) :171-174.
[13]雷勇.基于神经网络和专家系统的变电站故障诊断和处理系统的构想[J].福建电力与电工, 2003,(04) :21-24.
[14]吴长华,章少华.基于主动式知识库的专家系统建模和推理研究[J].杭州电子工业学院学报, 2001,(01) :30-34.
[15]吴凌云,王华. BP神经网络专家系统在故障诊断中的应用[J].信息技术, 2003, (02):66-68.
[16]朱永利,王艳,耿兰芹,苏丹.基于贝叶斯网络的电网故障诊断[J]电力自动化设备, 2007,(07):33-37 .
[17]刘燕燕.基于模糊神经网络的信息融合在电网故障诊断中的应用[J].继电器, 2005, (09):9-57 .
[18]郭创新,游家训,彭明伟,唐跃中,刘毅,陈济.基于面向元件神经网络与模糊积分融合技术的电网故障智能诊断[J]电工技术学报, 2010,(09):183-190 .
[19]赵爽,任建文.电网故障诊断系统的一种设计与实现[J].华东电力, 2003, (11):19-21.
[20]陈勇.智能技术在电网故障诊断中的应用[J].江苏电机工程, 2007, (04):39-42 .
[21]郭创新,朱传柏,曹一家.电力系统故障诊断的研究现状与发展趋势[J].电力系统自动化, 2006, 30( 8) : 98-103.
[22]梁循.数据挖掘算法与应用[M] .北京:北京大学出版社,2006:20-25.
[23] Rodrigues-Ortiz G, Fernandez-Espinosa V.Data mining techniques to classify energy demand[J].International Journal of Power and Energy System,1999,19(2):168-172.
[24]顾黎强,袁一鸣.数据挖掘技术在电网调度事故决策中的应用[J].供用电.2007,24(5):17-35.
[25]廖志伟,孙雅明.数据挖掘技术及其在电力系统中的应用[J].电力系统自动化.2001,25(11):62-66.
[26]孙卫祥.基于数据挖掘与信息融合的故障诊断方法研究[D]上海交通大学, 2006 .
[27] Lambert-Tones G. Application of Rough Set in Power System Control Center Data Mining[J] .Proceeding of the First International Conference on Machine Learning and Cybernetics. Piscataway. 2002 :627-631 .
[28]聂倩雯;高玮.基于关联规则数据挖掘技术的电网故障诊断[J].电力系统保护与控制.2009,37(9):8-19.
[29]张伯明,陈寿孙.高等电力网络分析[M].北京:清华大学出版社,1996:50-56.
[30]王志鹏.基于信息融合技术的故障诊断方法的研究及应用[D].大连理工大学, 2001 .
[31]刘毅,高振兴,郭创新,彭明伟.一种考虑多层信息融合的电网故障诊断辅助决策方法[J].电力系统保护与控制, 2010,(24) .
[32]赵熙临,周建中,付波,刘辉.基于信息融合技术的电网故障诊断方法[J].华中科技大学学报(自然科学版), 2009, (03):98-101 .
[33]江振华,程时杰.基于开关逻辑的电力系统图形和操作票自动生成系统[J].电力自动化设备,1999,19(3):12-14.
[34]朱奕.基于规则推理的电气防误操作评价系统[J].自动化技术与应用,2000,(2):19.
[35]刘蔚,杨宛辉.操作逻辑函数在操作票专家系统中的应用[J].电力系统及其自动化学报,1999,11(4):39-43