电力系统可靠性裕度评估
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摘要
随着经济的增长,电网向远距离、超高压甚至特高压方向的发展也越来越快,网络的规模日益庞大,结构也日益复杂。电力系统取得巨大的联网效益,但是同时承受着更大的潜在风险。确定性准则在大电网的规划和运行中受到了诸多限制,因此需要一些新的方法和观点来全面反映电网的状态,如需要考虑电网的一些随机事件等。本文主要研究了基于蒙特卡洛模拟法离线建立可靠性裕度参考系(即可靠性裕度标尺),将新的运行状态同参考系进行比较进而评估系统可靠性裕度。并在直接蒙特卡洛仿真的基础上加入了方差减小技术,即相关抽样、对偶抽样、匕首抽样三种方法,使得仿真速度加快。然后分析了年度指标下的可靠性指标,建立了负荷的分级模型,在计算中采用该模型可使指标的计算更加准确。
本文在最后采用了网络均衡熵这个指标来评估系统可靠性。该指标是通过计算系统的功能重要度和结构重要度二者结合得到的,它可从整体上反映电力系统网络的均衡性。熵值越大,网络均衡度越高,网络负荷分布越均衡,此时如果系统中的一部分元件发生故障则不会给系统带来太大的损失,因此系统的可靠性裕度越大。将网络均衡熵同前面的期望缺供电量EENS相结合对IEEE-24节点算例进行改造和扩建。通过数据分析可得到,在评估中引入该指标后,对系统的可靠性分析将更加全面,从而对操作者的判断提供更加详细的信息。
With economic growth, power to the remote, high pressure and even the direction of the development of UHV faster and faster, the network increasingly large scale, structure and sophistication. Interconnection power system has made great benefits, but also bear greater risks, deterministic criterion in bulk power system planning and operation by the many restrictions, so need some new methods and ideas to fully reflect the state power grid, such as the need to consider the power of some random events. This paper studies establish the reliability reference cases off-line based on Monte Carlo simulation (ie, scale of reliability margin),then compared new operational status with the reference cases in order to assess the new status reliability margin. And based on the direct Monte Carlo simulation added variance reduction technique, that is related to correlated sampling, antithetic sampling, dagger sampling three methods, making the simulation faster. And analyzed the annual target reliability index under the established classification of the load model, the model used in the calculation allows the calculation of more accurate indicators.
In this paper,at last use the index of network equilibrium entropy to assess system reliability. The index is an important function of the system by calculating the degree of importance and structure of a combination of both to get, it can reflect the overall balance of power system network. The greater entropy the higher of the degree of network equilibrium, the more balanced load distribution network, at this time if the system is part of the system component failure will not bring too much loss, so the greater the reliability of the system margin. Combination Entropy of the network with the previous expectation of a balanced energy not supplied EENS on IEEE-24 bus test case for reform and expansion. Through data analysis, the introduction of the indicators in assessing provide more detailed information for the operator to judge.
本文在最后采用了网络均衡熵这个指标来评估系统可靠性。该指标是通过计算系统的功能重要度和结构重要度二者结合得到的,它可从整体上反映电力系统网络的均衡性。熵值越大,网络均衡度越高,网络负荷分布越均衡,此时如果系统中的一部分元件发生故障则不会给系统带来太大的损失,因此系统的可靠性裕度越大。将网络均衡熵同前面的期望缺供电量EENS相结合对IEEE-24节点算例进行改造和扩建。通过数据分析可得到,在评估中引入该指标后,对系统的可靠性分析将更加全面,从而对操作者的判断提供更加详细的信息。
With economic growth, power to the remote, high pressure and even the direction of the development of UHV faster and faster, the network increasingly large scale, structure and sophistication. Interconnection power system has made great benefits, but also bear greater risks, deterministic criterion in bulk power system planning and operation by the many restrictions, so need some new methods and ideas to fully reflect the state power grid, such as the need to consider the power of some random events. This paper studies establish the reliability reference cases off-line based on Monte Carlo simulation (ie, scale of reliability margin),then compared new operational status with the reference cases in order to assess the new status reliability margin. And based on the direct Monte Carlo simulation added variance reduction technique, that is related to correlated sampling, antithetic sampling, dagger sampling three methods, making the simulation faster. And analyzed the annual target reliability index under the established classification of the load model, the model used in the calculation allows the calculation of more accurate indicators.
In this paper,at last use the index of network equilibrium entropy to assess system reliability. The index is an important function of the system by calculating the degree of importance and structure of a combination of both to get, it can reflect the overall balance of power system network. The greater entropy the higher of the degree of network equilibrium, the more balanced load distribution network, at this time if the system is part of the system component failure will not bring too much loss, so the greater the reliability of the system margin. Combination Entropy of the network with the previous expectation of a balanced energy not supplied EENS on IEEE-24 bus test case for reform and expansion. Through data analysis, the introduction of the indicators in assessing provide more detailed information for the operator to judge.
引文
[1]李文沅.电力系统风险评估—模型、方法和应用.北京:科学出版社,2006
[2]郭永基.电力系统可靠性分析.北京:清华大学出版社, 2003
[3] IEEE/CIGRE联合工作组,Definition and classification of power system stability[J]. IEEE Transactions on Power System 2004 IEEE, 19(3):1387-1401
[4] M T Schiling,M B D C Filho,A M L D Silva,etc.An integrated approach to power system reliability assessment [J].Electrical Power & Energy System,1995,17(6):381-390
[5]王超,徐政,高鹏,等.大电网可靠性评估指标体系探讨.电力系统及其自动化学报, 2007,19(1):42-48
[6]黄强,徐田.电网安全风险的调度应对体系研究[J] .华东电力,2006(8):11.12
[7] Zhu J Z.Optimal power system steady-state security regions with fuzzy constraints[C].IEEE power Engineering Society Winter Meeting.New York,USA,2002:1095-1099
[8] Hiroshi Ohtake,Katsuyuki Kimura.A Technique for Optimal Shut Capacitor Reallocation Considering Voltage Stability in N-1 Contingencies[J].Power Engineering Society General Meeting,2007.IEEE,1-6
[9] R.Y. Rubinstein, Simulation and the Monte Carlo Method,Wiley, 1981
[10] J. D. McCalley, A. A. Fouad, B. L. Agrawal, and R. G. Farmer,“A risk-based security index for determining operating limits in stabilitylimited electric power systems,”IEEE Trans. Power Syst., vol. 12, pp.1210–1217, Aug. 1997
[11] Kundur P,Paserba J.Definition and classification of power system stability IEEE/CIGRE joint task force on stability terms and definitions[J].IEEE Transactions on Power Systems,2004(19):1387-1401
[12]金玉琪,张浩,王函韵.基于“N-1”准则的安全稳定预控在电网运行中的运用.华东电力.2007,25(4),92-95
[13]陆波,唐国庆.基于风险的安全评估方法在电力系统中的应用.电力系统自动化.2000.11(25),61-64
[14]赵渊,周念成,谢开贵,等.大电力系统可靠性评估的系统状态抽取方法研究.中国电力,2006,39(6):5-9
[15]王英,谈定中,王小英,张炎平,唐国庆.基于风险的暂态稳定性安全评估方法在电力系统中的应用.电网技术.2003,27(12),37-41
[16]宋云亭,郭永基,程林.大规模发输电系统充裕度评估的蒙特卡罗仿真.电网技术.2003,27(8),24-28
[17]赵渊,周家启,刘洋.发输电组合系统可靠性评估中的最优负荷削减模型分析.电网技术.2004,28(10),34-37
[18] D. S. Kirschen,D. Jayaweera,D. P. Nedic,R. N. Allan. A probabilistic indicator of system stress.IEEE Transactions on Power Systems,2004,19(3):1650-1657
[19] D. S. Kirschen, D. Jayaweera, D. P. Nedic, and R. N. Allan,“Probabilistic indicator of system stress,”in Proc. PMAPS’2002—7th Int. Conf.Probabilistic Methods Applied to Power Systems, Naples, Italy, Sept.2002,pp.65–71
[20] K. R. W. Bell, D. S. Kirschen, R. N. Allan, and P. Kelen,“Efficient Monte Carlo assessment of the value of security,”in Proc. 13th Power System Computation Conf., Trondheim, Norway, June 1999, pp. 81–87
[21]任惠.电力系统连锁故障风险分析.[博士学位论文].保定:华北电力大学电力工程系,2009
[22]肖刚,李天柁.系统可靠性分析中的蒙特卡洛方法.北京:科学出版社.2003
[23] G.S. Fishman and B.D. Huang,“Antithetic variates revisited”,Communication of the ACM, vol. 26, no. 11, pp.964–971, 1983
[24] H. Kumamoto, K. Tanaka, K. Inoue, and E.J. Henley,“Dagger-sampling Monte Carlo for system unavailabilityevaluation”, IEEE Trans. on Reliability, vol. R-29, no. 2,1980
[25] D. S. Kirschen, M. A. Rios, K. R. W. Bell, and R. N. Allan,“Selection of operating scenarios based on the value of security,”in Proc. PMAPS’2000—6th Int. Conf. Probabilistic Methods Applied to Power Systems, Madeira, Portugal, Sept. 2000
[26]刘洋.发输电系统可靠性评估的蒙特卡洛模型及算法研究.[硕士学位论文].重庆大学,2003
[27]周光亚,赵文,赵振全.多元统计分析(第一版),北京地质出版社,1982年
[28] A. Sankarakrishnan and R. Billinton,“Sequential Monte Carlo simulation for composite power system reliability analysis with time varying loads”, IEEE Trans on Power Systems, vol. 10, no. 3, pp. 1540–1545, 1995
[29]王华丽.基于熵聚类的RBF神经网络训练算法研究.[硕士学位论文].重庆:重庆大学计算机学院,2009
[30]阎长俊,王启家,初长庚.系统和熵.沈阳建筑工程学院学报,1997,13(2):212-216
[31] Bing Wang,Huanwen Tang,Chonghui Guo,Zhilong Xiu.Entronpy optimization of scale-free networks’robustness to random failures.Physica Section A,Statistical&Theoretical Physics,2006,vol.363:591-596
[32]伍悦滨,王芳,田海.基于信息熵的给水管网系统可靠性分析[J].哈尔滨工业大学学报, 2007, 39(2): 251-254
[33]谭跃进,吴俊.网络结构熵及其在非标度网络中的应用.系统工程理论与实践,2004,6(6):1-3
[34]张明媛,袁永博,周晶.基于网络均衡性的生命线系统抗灾能力分析.辽宁工程技术大学学报(自然科学版),2009,28(2):228-230
[35]李志民,李卫星,李勃龙.熵原理及其在电力系统可靠性中的应用[J].电力系统及其自动化学报, 2001, 13(3): 37-40
[36]黄渊,运输网络中相关流量的均衡问题.[硕士学位论文].四川大学数学学院,2006
[37]余旭涛,张在琛,毕国光.一种ad hoc网络可靠性度量——网络均衡度.应用科学学报,2005,23(6):582-585
[38]郭琦.电源规划风险评估方法研究[D].保定:华北电力大学, 2009
[39]陈慧南.数据结构—使用C++语言描述.北京:人民邮电出版社,2006
[40]于晓军. FACTS装置对电网的长期可靠性影响的研究.保定:华北电力大学, 2009
[2]郭永基.电力系统可靠性分析.北京:清华大学出版社, 2003
[3] IEEE/CIGRE联合工作组,Definition and classification of power system stability[J]. IEEE Transactions on Power System 2004 IEEE, 19(3):1387-1401
[4] M T Schiling,M B D C Filho,A M L D Silva,etc.An integrated approach to power system reliability assessment [J].Electrical Power & Energy System,1995,17(6):381-390
[5]王超,徐政,高鹏,等.大电网可靠性评估指标体系探讨.电力系统及其自动化学报, 2007,19(1):42-48
[6]黄强,徐田.电网安全风险的调度应对体系研究[J] .华东电力,2006(8):11.12
[7] Zhu J Z.Optimal power system steady-state security regions with fuzzy constraints[C].IEEE power Engineering Society Winter Meeting.New York,USA,2002:1095-1099
[8] Hiroshi Ohtake,Katsuyuki Kimura.A Technique for Optimal Shut Capacitor Reallocation Considering Voltage Stability in N-1 Contingencies[J].Power Engineering Society General Meeting,2007.IEEE,1-6
[9] R.Y. Rubinstein, Simulation and the Monte Carlo Method,Wiley, 1981
[10] J. D. McCalley, A. A. Fouad, B. L. Agrawal, and R. G. Farmer,“A risk-based security index for determining operating limits in stabilitylimited electric power systems,”IEEE Trans. Power Syst., vol. 12, pp.1210–1217, Aug. 1997
[11] Kundur P,Paserba J.Definition and classification of power system stability IEEE/CIGRE joint task force on stability terms and definitions[J].IEEE Transactions on Power Systems,2004(19):1387-1401
[12]金玉琪,张浩,王函韵.基于“N-1”准则的安全稳定预控在电网运行中的运用.华东电力.2007,25(4),92-95
[13]陆波,唐国庆.基于风险的安全评估方法在电力系统中的应用.电力系统自动化.2000.11(25),61-64
[14]赵渊,周念成,谢开贵,等.大电力系统可靠性评估的系统状态抽取方法研究.中国电力,2006,39(6):5-9
[15]王英,谈定中,王小英,张炎平,唐国庆.基于风险的暂态稳定性安全评估方法在电力系统中的应用.电网技术.2003,27(12),37-41
[16]宋云亭,郭永基,程林.大规模发输电系统充裕度评估的蒙特卡罗仿真.电网技术.2003,27(8),24-28
[17]赵渊,周家启,刘洋.发输电组合系统可靠性评估中的最优负荷削减模型分析.电网技术.2004,28(10),34-37
[18] D. S. Kirschen,D. Jayaweera,D. P. Nedic,R. N. Allan. A probabilistic indicator of system stress.IEEE Transactions on Power Systems,2004,19(3):1650-1657
[19] D. S. Kirschen, D. Jayaweera, D. P. Nedic, and R. N. Allan,“Probabilistic indicator of system stress,”in Proc. PMAPS’2002—7th Int. Conf.Probabilistic Methods Applied to Power Systems, Naples, Italy, Sept.2002,pp.65–71
[20] K. R. W. Bell, D. S. Kirschen, R. N. Allan, and P. Kelen,“Efficient Monte Carlo assessment of the value of security,”in Proc. 13th Power System Computation Conf., Trondheim, Norway, June 1999, pp. 81–87
[21]任惠.电力系统连锁故障风险分析.[博士学位论文].保定:华北电力大学电力工程系,2009
[22]肖刚,李天柁.系统可靠性分析中的蒙特卡洛方法.北京:科学出版社.2003
[23] G.S. Fishman and B.D. Huang,“Antithetic variates revisited”,Communication of the ACM, vol. 26, no. 11, pp.964–971, 1983
[24] H. Kumamoto, K. Tanaka, K. Inoue, and E.J. Henley,“Dagger-sampling Monte Carlo for system unavailabilityevaluation”, IEEE Trans. on Reliability, vol. R-29, no. 2,1980
[25] D. S. Kirschen, M. A. Rios, K. R. W. Bell, and R. N. Allan,“Selection of operating scenarios based on the value of security,”in Proc. PMAPS’2000—6th Int. Conf. Probabilistic Methods Applied to Power Systems, Madeira, Portugal, Sept. 2000
[26]刘洋.发输电系统可靠性评估的蒙特卡洛模型及算法研究.[硕士学位论文].重庆大学,2003
[27]周光亚,赵文,赵振全.多元统计分析(第一版),北京地质出版社,1982年
[28] A. Sankarakrishnan and R. Billinton,“Sequential Monte Carlo simulation for composite power system reliability analysis with time varying loads”, IEEE Trans on Power Systems, vol. 10, no. 3, pp. 1540–1545, 1995
[29]王华丽.基于熵聚类的RBF神经网络训练算法研究.[硕士学位论文].重庆:重庆大学计算机学院,2009
[30]阎长俊,王启家,初长庚.系统和熵.沈阳建筑工程学院学报,1997,13(2):212-216
[31] Bing Wang,Huanwen Tang,Chonghui Guo,Zhilong Xiu.Entronpy optimization of scale-free networks’robustness to random failures.Physica Section A,Statistical&Theoretical Physics,2006,vol.363:591-596
[32]伍悦滨,王芳,田海.基于信息熵的给水管网系统可靠性分析[J].哈尔滨工业大学学报, 2007, 39(2): 251-254
[33]谭跃进,吴俊.网络结构熵及其在非标度网络中的应用.系统工程理论与实践,2004,6(6):1-3
[34]张明媛,袁永博,周晶.基于网络均衡性的生命线系统抗灾能力分析.辽宁工程技术大学学报(自然科学版),2009,28(2):228-230
[35]李志民,李卫星,李勃龙.熵原理及其在电力系统可靠性中的应用[J].电力系统及其自动化学报, 2001, 13(3): 37-40
[36]黄渊,运输网络中相关流量的均衡问题.[硕士学位论文].四川大学数学学院,2006
[37]余旭涛,张在琛,毕国光.一种ad hoc网络可靠性度量——网络均衡度.应用科学学报,2005,23(6):582-585
[38]郭琦.电源规划风险评估方法研究[D].保定:华北电力大学, 2009
[39]陈慧南.数据结构—使用C++语言描述.北京:人民邮电出版社,2006
[40]于晓军. FACTS装置对电网的长期可靠性影响的研究.保定:华北电力大学, 2009