大电网极端故障情况下的稳定控制策略研究
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摘要
论文基于电网稳定性控制分散采集、协调调度、集中控制的发展趋势,以及长期超高压一线运行实践经验。在采用传统底层数学模型的基础上,提出一种可以在故障发生后短期内完全介入的,能够从全网架的尺度实施宏观控制的新型控制策略及其控制模型、优化算法。该控制策略在系统发生极端故障情况下,以稳态、暂态范畴的诸原理为依据,对故障后或故障发展过程中的系统进行紧急控制,使受损的系统能够恢复到稳定运行的状态。
在提升数值计算效能方面,为了能够大尺度地减少在电力系统故障情况下,系统稳定性分析模型的求解计算量,论文根据电力系统的特点,参考了启发式算法,如粒子群算法、鱼群算法、蚁群算法等,并经过综合分析在充分考虑了电力系统特点的前提下,尝试性地提出了旨在缩小求解过程中搜索范围的“购物”算法。
为了验证理论的可行性在仿真实验阶段,首先对河南电网“6.25”事故重点进行了暂态阶段的仿真分析,验证了论文所提出的暂态分析理论的实际可行性。其次,以05年海南电网崩溃的实时过程及数据为背景,在加入控制策略的情况下利用仿真平台仿真了海南电网故障的全过程。通过实验结果可以看出,在引入论文所提出的大电网极端故障情况下的控制策略后,海南仿真电网系统虽然经历了和实际情况相一致的连续故障的分阶段反复打击,但最终调整后的海南电网各参数依然可以满足稳定运行条件,海南电网仍然可以稳定的运行,由此证明论文所提出的电网稳定控制策略是可行的。
The paper is based on the trend of network stability control decentralized collection, coordination of scheduling and centralized control as well as the ultra-high pressure and long-term practical experience in running the front line. By introducing the traditional underlying mathematical model, the paper presents a new control strategy as well as its control model and optimization algorithm, which can get into entirely in a short term, and can be able to make macro-control in the respect of the entire network. The control strategy, which is used in extreme failure situation in the system, is based on the scope of the steady-state energy balance principle. It takes emergency control in the system both after the failure or failure in the development, enabling the damaged system to resume to the stable state of the operation.
In aspect of enhancing the effectiveness of numerical calculation, in order to greatly reduce the computation of system stability analysis model in power system fault conditions, according to the characteristics of the power system and fully taken into account the characteristics of the power system, the paper, which has refers to heuristic algorithm such as particle swarm optimization, fish-swarm algorithm, ant colony algorithm and so on, tentatively puts forward the 'shopping' algorithm to narrowing the scope of the search while solving.
At last, the paper takes advantage of VC language to build a simulation platform and take the classic example as a blueprint to verify its correctness. In the simulation stage, the paper takes transient phase of the simulation analys on Henan power network "6.25" incident and it proves the practical feasibility of transient analysis theory put forward by the paper. Secondly, having the real-time process and data of Hainan power grid collapse in 2005 as the background, by adding the control strategy, the paper has taken advantage of the simulation to replay the whole process of Hainan fault. From the results of the simulation, by using the control strategy in large power grids under extreme fault conditions which is put forward by the paper, in spite of the same as the real experience of reaptly consistent failure, the eventually adjusted Hainan power grid is still able to meet the parameters of the conditions of stable operation, so does the Hainan power is still in a good operation condition. Therefore, the power grid stability control strategy proposed by this paper, which has been well verified in the steady-state phase, is feasible.
在提升数值计算效能方面,为了能够大尺度地减少在电力系统故障情况下,系统稳定性分析模型的求解计算量,论文根据电力系统的特点,参考了启发式算法,如粒子群算法、鱼群算法、蚁群算法等,并经过综合分析在充分考虑了电力系统特点的前提下,尝试性地提出了旨在缩小求解过程中搜索范围的“购物”算法。
为了验证理论的可行性在仿真实验阶段,首先对河南电网“6.25”事故重点进行了暂态阶段的仿真分析,验证了论文所提出的暂态分析理论的实际可行性。其次,以05年海南电网崩溃的实时过程及数据为背景,在加入控制策略的情况下利用仿真平台仿真了海南电网故障的全过程。通过实验结果可以看出,在引入论文所提出的大电网极端故障情况下的控制策略后,海南仿真电网系统虽然经历了和实际情况相一致的连续故障的分阶段反复打击,但最终调整后的海南电网各参数依然可以满足稳定运行条件,海南电网仍然可以稳定的运行,由此证明论文所提出的电网稳定控制策略是可行的。
The paper is based on the trend of network stability control decentralized collection, coordination of scheduling and centralized control as well as the ultra-high pressure and long-term practical experience in running the front line. By introducing the traditional underlying mathematical model, the paper presents a new control strategy as well as its control model and optimization algorithm, which can get into entirely in a short term, and can be able to make macro-control in the respect of the entire network. The control strategy, which is used in extreme failure situation in the system, is based on the scope of the steady-state energy balance principle. It takes emergency control in the system both after the failure or failure in the development, enabling the damaged system to resume to the stable state of the operation.
In aspect of enhancing the effectiveness of numerical calculation, in order to greatly reduce the computation of system stability analysis model in power system fault conditions, according to the characteristics of the power system and fully taken into account the characteristics of the power system, the paper, which has refers to heuristic algorithm such as particle swarm optimization, fish-swarm algorithm, ant colony algorithm and so on, tentatively puts forward the 'shopping' algorithm to narrowing the scope of the search while solving.
At last, the paper takes advantage of VC language to build a simulation platform and take the classic example as a blueprint to verify its correctness. In the simulation stage, the paper takes transient phase of the simulation analys on Henan power network "6.25" incident and it proves the practical feasibility of transient analysis theory put forward by the paper. Secondly, having the real-time process and data of Hainan power grid collapse in 2005 as the background, by adding the control strategy, the paper has taken advantage of the simulation to replay the whole process of Hainan fault. From the results of the simulation, by using the control strategy in large power grids under extreme fault conditions which is put forward by the paper, in spite of the same as the real experience of reaptly consistent failure, the eventually adjusted Hainan power grid is still able to meet the parameters of the conditions of stable operation, so does the Hainan power is still in a good operation condition. Therefore, the power grid stability control strategy proposed by this paper, which has been well verified in the steady-state phase, is feasible.
引文
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[2]甘德强,胡江溢,韩祯祥。2003年国际若干停电事故思考[J].电力系统自动化,2004,28(3):1-5.
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[4]周新风,施贵荣,赵刚.华北电网“4.28”事故分析[J].电力系统自动化,2000(6):61-64.
[5]宋军英,徐宇新,李西泉,等.湖南电网“2.10”低频事故分析[J].湖南电力,2005,25(5):4-6.
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[7]HE T,KOLURI S,MANDAL S,et al.Identification of Weak locations in bulk transmission systems using voltage stability margin index[C].Proceedings of IEEE PES 2004 General Meeting,Vo12.Denver(CO):2004.1814-1819.
[8]LADHAINI S S,ROSEHART W.Feasibility of Under Voltage load shedding for voltage stability in a deregulated Electric utility industry[C].Proceedings of IEEE PES 2004General Meeting,Vo12.Denver(CO):2004.1597-1602.
[9]SAVULESCU S C.Real-time Detection of risk of Blackout[C].Proceedings of IEEE PES 2004 General Meeting,Vo1.2 Denver(CO):2004.881-882.
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[11]刘冰.基于“三道防线”的广域保护系统及算法研究[J],广东电力,2005,18(6):5-11。
[12]徐泰山,许剑冰,鲍颜红,等.互联电网预防控制和紧急控制在线预决策系统[J].电力系统自动化,2006,30(7):1-5.
[13]LARSSON S,EKE.The Black-out in Southem Sweden and Eastern Demark in September 23,2003[C].Proceedings of IEEE PES 2004 General Meeting,Vo12.Denver(CO):2004.1668-1672.
[14]LIU C C,Strategic power Infrastructrue defense(SPID)[C].Proceedings of IEEE PES 2002 Trans Distribution Conf,Vo1.1 Yokahama(Japan):2002.500-502.
[15]LIU C C,JUNG J,HEYDT G T,et al.The Strategic Power Infrastructure Defense (SPID) System:a Conceptual Design[J].IEEE Control System Magazine,2002(8):40-52.
[16]Chen-Ching Liu.Strategic power infrastructure defense(SPID):a wide area protection and control system[C].Transmission and Distribution Conference and Exhibition 2002:Asia Pacific.IEEE/PES Volume 1,6-10 Oct.2002 Page(s):500- 502[17]Chen-Ching Li.Strategic power infrastructure defense(SPID)[C].Power Engineering Society General Meeting,IEEE,6-10 June,2004,Page(s):3-6.
[17]Chen-Ching Li.Strategic power infrastructure defense(SPID)[C].Power Engineering Society General Meeting,IEEE,6-10 June,2004,Page(s):3-6.
[18]南京供电公司.500kV三汊湾变电站现场运行规程[版本号[2.1][Z].南京供电公司,2006。
[19]江苏电力调度通信中心.江苏电网安全稳定实时预警及协调防御EACCS系统运行管理规定[Z]。江苏电力调度通信中心,2007。
[20]赵希人,彭秀艳,姜广宇。基于神经网络方法的大型电网短期负荷预报[J].系统仿真学报,2006,18(6):1677-1680.
[21]任先成,韩富春,樊丽丽.电力系统状态估计的快速分解法研究[J].太原理工大学学报,2002,33(5):485-487.
[22]郑斌祥,席裕庚.面向电力系统的数据挖掘研究[J].电气自动化,2000,6:4-8.
[23]WILSON S.The Animal Path to A1.Proceedings of the first international conference on the Simulation of adaptive behavior[R].Cambridge:M IT Press,1991.
[24]Bonabeaue,Theraulazg.SwarmSmarts.ScientificAmerican[J],2000,282(3):72-79.
[25]李军军,王锡淮。一种改进的微粒群优化算法。第五届全球智能控制与自动化大会[J]。2004:354-356。
[26]张丽平.粒子群优化算法的理论及实践[D]:[博士学位论文].杭州:浙江大学,2005。
[27]殷志锋,田亚菲.基于人工鱼群算法的IIR数字滤波器设计[J]。信息技术,2006(7):78-82。
[28]薛婷.粒子群优化算法的研究与改进[D].[硕士学位论文]。大连:大连海事大学,2008.
[29]李莉.基于遗传算法的神经网络在织物染色配色中的应用研究[D].青岛大学硕士学位论文,2007.
[30]蒋宇。基于05年海南电网崩溃事故的电网稳定控制策略仿真研究[D].东南大学工程硕士学位论文,2009.
[31]朱方,赵红光,增煌,等。大区电网互联对电力系统动态稳定性的影响[J].中国电机工程学报,2007,27(1):1-7。
[32]李光琦.电力系统暂态分析(第二版)[M].中国电力出版社,1995。
[33]诸俊伟。电力系统分析(上册)[M].中国电力出版社,1995.
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