中国电网停电事故时间间隔的统计及分布特性分析
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摘要
为研究中国电网停电事故的复杂动态特性,分析了中国电网停电事故时间间隔的分布特性.首先,对中国电网1981～2014年的停电事故的时间间隔进行了统计分析和正态性检验,指出了中国电网停电事故的时间间隔近似满足幂律分布.其次,利用重标方差(rescaled variance, V/S)方法对中国电网停电事故的时间间隔序列进行了相关性分析,指出了中国电网停电事故的时间间隔序列具有长程正相关性和统计自相似性.最后,给出了电网停电事故时间间隔分布特性的意义.
To study the complex dynamic characteristics of blackouts in Chinese power grid, the distribution characteristics of time intervals of blackouts in Chinese power grid are researched. Firstly, the time intervals of blackouts in Chinese power grid from 1981–2014 are analyzed by statistical analysis and normality test. It is proved that the time intervals of blackouts in Chinese power grid approximately satisfies the power-law distribution. Secondly, utilizing the V/S method, the correlation of time intervals of blackouts in Chinese power grid is researched. It is proved that the time intervals of blackouts in Chinese power grid have the strong positive correlation and self-similarity on long time scale. Finally, the significance of distribution characteristics of time intervals of blackouts in Chinese power grid is given.
To study the complex dynamic characteristics of blackouts in Chinese power grid, the distribution characteristics of time intervals of blackouts in Chinese power grid are researched. Firstly, the time intervals of blackouts in Chinese power grid from 1981–2014 are analyzed by statistical analysis and normality test. It is proved that the time intervals of blackouts in Chinese power grid approximately satisfies the power-law distribution. Secondly, utilizing the V/S method, the correlation of time intervals of blackouts in Chinese power grid is researched. It is proved that the time intervals of blackouts in Chinese power grid have the strong positive correlation and self-similarity on long time scale. Finally, the significance of distribution characteristics of time intervals of blackouts in Chinese power grid is given.
引文
1郭剑波,于群,贺庆.电力系统复杂性理论初探.北京:科学出版社, 2012. 149–150
2 胥威汀,刘俊勇,李旻,等.避免电网连锁解列的全局协调控制策略.电力自动化设备, 2013, 33:33–39
3 于群,张敏,曹娜,等.基于模糊元胞自动机的电网连锁故障控制策略.电力自动化设备, 2016, 36:90–95
4 曾辉,孙峰,李铁,等.澳大利亚“9?28”大停电事故分析及对中国启示.电力系统自动化, 2017, 41:1–6
5 Carreras B A, Newman D E, Dobson I, et al. Initial evidence for self-organized criticality in electric power blackouts. In:Proceedings of 33rd Annual Hawaii International Conference on System Science. Maui, 2000. 1–6
6 Chen J, Thorp J S, Parashar M. Analysis of electric power system disturbance data. In:Proceedings of 34th Hawaii International Conference on System Science. Maui, 2001. 738–744
7 Carreras B A, Newman D E, Dobson I, et al. Evidence for self-organized criticality in electric power blackouts. In:Proceedings of 34th Hawaii International Conference on System Science. Maui, 2001. 705–709
8 Carreras B A, Newman D E, Dobson I, et al. Evidence for self-organized criticality in a time series of electric power system blackouts. IEEE Trans Circuits Syst I, 2004, 51:1733–1740
9 Hines P, Apt J, Talukdar S. Large blackouts in North America:Historical trends and policy implications. Energy Policy, 2009, 37:5249–5259
10 Cornforth D. Long tails from the distribution of 23 years of electrical disturbance data. In:Proceedings of 2009 IEEE/PES Power Systems Conference and Exposition. Seattle, 2009. 1–8
11 Carreras B A, Newman D E, Dobson I. North American blackout time series statistics and implications for blackout risk. IEEE Trans Power Syst,2016, 31:4406–4414
12 于群,郭剑波.中国电网停电事故统计与自组织临界性特征.电力系统自动化, 2006, 30:16–21
13 于群,郭剑波.中国电力系统停电事故自组织临界性的研究.电网技术, 2006, 30:1–5
14 梅生伟,薛安成,张雪敏.电力系统自组织临界特性与大电网安全.北京:清华大学出版社, 2009. 16–60
15 晁岱峰,杨军选,苏盛,等.濮阳配电网故障的自组织临界性及其诱因.电网技术, 2011, 35:72–75
16 Boffetta G, Carbone V, Giuliani P, et al. Power laws in solar flares:Self-organized criticality or turbulence? Phys Rev Lett, 1999, 83:4662–4665
17 Weron R, Simonsen I. Blackouts, risk, and fat-tailed distributions. In:Proceedings of 3rd Nikkei Econophysics Symposium. Tokyo, 2005. 215–219
18徐立新,杨建美,潮铸,等.电网故障时间间隔的统计分布及非线性特征分析.电网技术, 2013, 37:3482–3488
19 于群.电力系统大停电的自组织临界特性研究.中国电力科学研究院, 2010
20 国家电力调度通信中心.全国电网典型事故分析(1988~1998).北京:中国电力出版社, 2000
21 国家电力调度通信中心.全国电网典型事故分析(1999~2007).北京:中国电力出版社, 2008
22 国家电网公司安全监察部.国家电网公司2007年安全生产事故报告.北京:中国电力出版社, 2007
23 国家电网公司安全监察部.国家电网公司2008年安全生产事故报告.北京:中国电力出版社, 2009
24 国家电网公司安全监察部.国家电网公司2009年安全生产事故报告.北京:中国电力出版社, 2010
25 国家电网公司安全监察部.国家电网公司2010年安全生产事故报告.北京:中国电力出版社, 2011
26 国家电网公司安全监察质量部.国家电网公司2011年安全生产事故报告.北京:中国电力出版社, 2012
27 国家电网公司安全监察质量部.国家电网公司2012年安全生产事故报告.北京:中国电力出版社, 2013
28 国家电网公司安全监察质量部.国家电网公司2013年安全生产事故报告.北京:中国电力出版社, 2014
29 国家电网公司安全监察质量部.国家电网公司2014年安全生产事故报告.北京:中国电力出版社, 2015
30 Clauset A, Shalizi C R, Newman M E J. Power-law distributions in empirical data. SIAM Rev, 2009, 51:661–703
31 何兴强,李仲飞.上证股市收益的长期记忆:基于V/S的经验分析.系统工程理论与实践, 2006, 26:47–54
32 乔美英,陈鑫,兰建义.基于V/S分析的瓦斯涌出量分形特性研究.中国煤炭, 2014, 40:104–110
33 Giraitis L, Kokoszka P, Leipus R, et al. Rescaled variance and related tests for long memory in volatility and levels. J Econom, 2003, 112:265–294
34于群,屈玉清,石良.基于相对值法和Hurst指数的电网停电事故自相关性分析.电力系统自动化, 2018, 42:55–60
35 Peters E E. Fractal Market Analysis. New York:John Wiley&Sons, Inc., 1994
36 彼得斯·埃德加·E,著.储海林,殷勤,译.分形市场分析——将混沌理论应用到投资于经济理论上.北京:经济科学出版社, 2002
37 于群,郭剑波.自组织临界性与大停电事故预测.中国电力, 2011, 44:21–25
38 于群,石良,曹娜,等.广义极值理论在大停电事故损失负荷预测中的应用.电力系统自动化, 2016, 40:71–77
2 胥威汀,刘俊勇,李旻,等.避免电网连锁解列的全局协调控制策略.电力自动化设备, 2013, 33:33–39
3 于群,张敏,曹娜,等.基于模糊元胞自动机的电网连锁故障控制策略.电力自动化设备, 2016, 36:90–95
4 曾辉,孙峰,李铁,等.澳大利亚“9?28”大停电事故分析及对中国启示.电力系统自动化, 2017, 41:1–6
5 Carreras B A, Newman D E, Dobson I, et al. Initial evidence for self-organized criticality in electric power blackouts. In:Proceedings of 33rd Annual Hawaii International Conference on System Science. Maui, 2000. 1–6
6 Chen J, Thorp J S, Parashar M. Analysis of electric power system disturbance data. In:Proceedings of 34th Hawaii International Conference on System Science. Maui, 2001. 738–744
7 Carreras B A, Newman D E, Dobson I, et al. Evidence for self-organized criticality in electric power blackouts. In:Proceedings of 34th Hawaii International Conference on System Science. Maui, 2001. 705–709
8 Carreras B A, Newman D E, Dobson I, et al. Evidence for self-organized criticality in a time series of electric power system blackouts. IEEE Trans Circuits Syst I, 2004, 51:1733–1740
9 Hines P, Apt J, Talukdar S. Large blackouts in North America:Historical trends and policy implications. Energy Policy, 2009, 37:5249–5259
10 Cornforth D. Long tails from the distribution of 23 years of electrical disturbance data. In:Proceedings of 2009 IEEE/PES Power Systems Conference and Exposition. Seattle, 2009. 1–8
11 Carreras B A, Newman D E, Dobson I. North American blackout time series statistics and implications for blackout risk. IEEE Trans Power Syst,2016, 31:4406–4414
12 于群,郭剑波.中国电网停电事故统计与自组织临界性特征.电力系统自动化, 2006, 30:16–21
13 于群,郭剑波.中国电力系统停电事故自组织临界性的研究.电网技术, 2006, 30:1–5
14 梅生伟,薛安成,张雪敏.电力系统自组织临界特性与大电网安全.北京:清华大学出版社, 2009. 16–60
15 晁岱峰,杨军选,苏盛,等.濮阳配电网故障的自组织临界性及其诱因.电网技术, 2011, 35:72–75
16 Boffetta G, Carbone V, Giuliani P, et al. Power laws in solar flares:Self-organized criticality or turbulence? Phys Rev Lett, 1999, 83:4662–4665
17 Weron R, Simonsen I. Blackouts, risk, and fat-tailed distributions. In:Proceedings of 3rd Nikkei Econophysics Symposium. Tokyo, 2005. 215–219
18徐立新,杨建美,潮铸,等.电网故障时间间隔的统计分布及非线性特征分析.电网技术, 2013, 37:3482–3488
19 于群.电力系统大停电的自组织临界特性研究.中国电力科学研究院, 2010
20 国家电力调度通信中心.全国电网典型事故分析(1988~1998).北京:中国电力出版社, 2000
21 国家电力调度通信中心.全国电网典型事故分析(1999~2007).北京:中国电力出版社, 2008
22 国家电网公司安全监察部.国家电网公司2007年安全生产事故报告.北京:中国电力出版社, 2007
23 国家电网公司安全监察部.国家电网公司2008年安全生产事故报告.北京:中国电力出版社, 2009
24 国家电网公司安全监察部.国家电网公司2009年安全生产事故报告.北京:中国电力出版社, 2010
25 国家电网公司安全监察部.国家电网公司2010年安全生产事故报告.北京:中国电力出版社, 2011
26 国家电网公司安全监察质量部.国家电网公司2011年安全生产事故报告.北京:中国电力出版社, 2012
27 国家电网公司安全监察质量部.国家电网公司2012年安全生产事故报告.北京:中国电力出版社, 2013
28 国家电网公司安全监察质量部.国家电网公司2013年安全生产事故报告.北京:中国电力出版社, 2014
29 国家电网公司安全监察质量部.国家电网公司2014年安全生产事故报告.北京:中国电力出版社, 2015
30 Clauset A, Shalizi C R, Newman M E J. Power-law distributions in empirical data. SIAM Rev, 2009, 51:661–703
31 何兴强,李仲飞.上证股市收益的长期记忆:基于V/S的经验分析.系统工程理论与实践, 2006, 26:47–54
32 乔美英,陈鑫,兰建义.基于V/S分析的瓦斯涌出量分形特性研究.中国煤炭, 2014, 40:104–110
33 Giraitis L, Kokoszka P, Leipus R, et al. Rescaled variance and related tests for long memory in volatility and levels. J Econom, 2003, 112:265–294
34于群,屈玉清,石良.基于相对值法和Hurst指数的电网停电事故自相关性分析.电力系统自动化, 2018, 42:55–60
35 Peters E E. Fractal Market Analysis. New York:John Wiley&Sons, Inc., 1994
36 彼得斯·埃德加·E,著.储海林,殷勤,译.分形市场分析——将混沌理论应用到投资于经济理论上.北京:经济科学出版社, 2002
37 于群,郭剑波.自组织临界性与大停电事故预测.中国电力, 2011, 44:21–25
38 于群,石良,曹娜,等.广义极值理论在大停电事故损失负荷预测中的应用.电力系统自动化, 2016, 40:71–77