多次磁暴下特高压电网GIC统计规律研究
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摘要
探明灾害性地磁感应电流(geomagnetically induced currents,GIC)在电网中的分布特征对于准确评估极端空间天气风险具有重要意义。该文依据Dst指数选取多次强磁暴数据,分别计算三华地区感应地电场和特高压(ultra-highvoltage,UHV)规划电网各变电站的GIC,再以这些计算值作为样本数据,通过各变电站GIC贡献率P、回归系数G以及概率分布参数a描述电网GIC的空间分布;参考可决系数R,得出地电场和GIC的概率分布模型,并据此预测各节点三相GIC的"百年一遇"值。结果表明,感应地电场符合对数正态分布,电网节点GIC符合韦伯分布;统计结果可反映电网遭受磁暴侵害的严重程度,为进一步评估电网GIC风险、制定合理的防治措施提供依据。
Ascertaining the distribution characteristics of disastrous geomagnetically induced currents(GIC) in a power grid is important to accurately evaluate the effects of extreme space weather on power grids. This paper presented the induced geoelectric fields in northern, center and eastern areas of China(Sanhua) and GIC at each substation in the ultra-high-voltage power grid during strong geomagnetic storms selected by the Dst index. The GIC contribution rate P for each substation, the regression coefficient G, and the parameter a of probability distribution were calculated to describe the spatial distribution of GIC in the power grid on the basis of sample data.The probability distribution model of geoelectric fields and GIC in the power grid were determined with reference to the R-squared value(R), and the 100-year GIC values of three-phases in each node were predicted accordingly. The results show that the logarithmic normal distribution and Weibull distribution are suitable probability distribution models for geoelectric field and GIC in the power grid respectively. The results reflect the severity of the damage of power grids by geomagnetic storms which can also provide the basis for controlling and evaluating the effects of GIC on a power grid.
Ascertaining the distribution characteristics of disastrous geomagnetically induced currents(GIC) in a power grid is important to accurately evaluate the effects of extreme space weather on power grids. This paper presented the induced geoelectric fields in northern, center and eastern areas of China(Sanhua) and GIC at each substation in the ultra-high-voltage power grid during strong geomagnetic storms selected by the Dst index. The GIC contribution rate P for each substation, the regression coefficient G, and the parameter a of probability distribution were calculated to describe the spatial distribution of GIC in the power grid on the basis of sample data.The probability distribution model of geoelectric fields and GIC in the power grid were determined with reference to the R-squared value(R), and the 100-year GIC values of three-phases in each node were predicted accordingly. The results show that the logarithmic normal distribution and Weibull distribution are suitable probability distribution models for geoelectric field and GIC in the power grid respectively. The results reflect the severity of the damage of power grids by geomagnetic storms which can also provide the basis for controlling and evaluating the effects of GIC on a power grid.
引文
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[12]Viljanen A,Pirjola R,Prácser E,et al.Geomagnetically induced currents in Europe.Modelled occurrence in a continent-wide power grid[J].Journal of Space Weather and Space Climate,2014,4:A09.
[13]Viljanen A,Pirjola R.Influence of spatial variations of the geoelectric field on geomagnetically induced currents[J].Journal of Space Weather and Space Climate,2017,7:A22.
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[15]Danskin D W,Lotz S I.Analysis of geomagnetic hourly ranges[J].Space Weather,2015,13(8):458-468.
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[17]Pulkkinen A,Pirjola R,Viljanen A.Statistics of extreme geomagnetically induced current events[J].Space Weather,2008,6(7):S07001.
[18]Pulkkinen A,Bernabeu E,Eichner J,et al.Generation of100-year geomagnetically induced current scenarios[J].Space Weather,2012,10(4):S04003.
[19]Barbosa C S,Caraballo R,Alves L R,et al.The Tsallis statistical distribution applied to geomagnetically induced currents[J].Space Weather,2017,15(9):1094-1101.
[20]刘连光,吴伟丽.磁暴影响电力系统安全风险评估思路与理论框架[J].中国电机工程学报,2014,34(10):1583-1591.Liu Lianguang,Wu Weili.Security risk assessment ideas and theoretical framework for power system considering geomagnetic storm[J].Proceedings of the CSEE,2014,34(10):1583-1591(in Chinese).
[2]Barbosa C S,Hartmann G A,Pinheiro K J.Numerical modeling of geomagnetically induced currents in a Brazilian transmission line[J].Advances in Space Research,2015,55(4):1168-1179.
[3]Torta J M,Marsal S,Quintana M.Assessing the hazard from geomagnetically induced currents to the entire high-voltage power network in Spain[J].Earth,Planets and Space,2014,66(1):87.
[4]郑宽,刘连光,Boteler D H,等.多电压等级电网的GIC-Benchmark建模方法[J].中国电机工程学报,2013,33(16):179-186.Zheng Kuan,Liu Lianguang,Boteler D H,et al.Modelling geomagnetically induced currents in multiple voltage levels of a power system illustrated using the GIC-Benchmark case[J].Proceedings of the CSEE,2013,33(16):179-186(in Chinese).
[5]刘春明.中低纬电网地磁感应电流及其评估方法研究[D].北京:华北电力大学,2009.Liu Chunming.Mid-low latitude power grid geomagnetically induced currents and its assessing method[D].Beijing:North China Electric Power University,2009(in Chinese).
[6]刘连光,刘春明,张冰.磁暴对我国特高压电网的影响研究[J].电网技术,2009,33(11):1-5.Liu Lianguang,Liu Chunming,Zhang Bing.Effects of geomagnetic storm on UHV power grids in China[J].Power System Technology,2009,33(11):1-5(in Chinese).
[7]Trichtchenko L,Boteler D H.Effects of recent geomagnetic storms on power systems[C]//Proceedings of the 7th International Symposium on Electromagnetic Compatibility and Electromagnetic Ecology.SaintPetersburg,Russia:IEEE,2007:265-268.
[8]Barbosa C,Alves L,Caraballo R,et al.Analysis of x geomagnetically induced currents at a low-latitude region over the solar cycles 23 and 24:comparison between measurements and calculations[J].Journal of Space Weather and Space Climate,2015,5:A35.
[9]Blake S P,Gallagher P T,Mc Cauley J,et al.Geomagnetically induced currents in the Irish power network during geomagnetic storms[J].Space Weather,2016,14(12):1136-1154.
[10]陈鸿飞,徐文耀.1998年5月磁暴磁层电流体系的地磁效应分析[J].地球物理学报,2001,44(4):490-499.Chen Hongfei,Xu Wenyao.Variations of inner magnetospheric currents during the magnetic storm of May 1998[J].Chinese Journal of Geophysics,2001,44(4):490-499(in Chinese).
[11]刘连光,郭世晓,魏恺,等.基于全节点模型的三华电网地磁感应电流计算[J].电网技术,2014,38(7):1946-1952.Liu Lianguang,Guo Shixiao,Wei Kai,et al.Calculation of geomagnetically induced currents in interconnected North China-Central China-East China power grid based on full-node GIC model[J].Power System Technology,2014,38(7):1946-1952(in Chinese).
[12]Viljanen A,Pirjola R,Prácser E,et al.Geomagnetically induced currents in Europe.Modelled occurrence in a continent-wide power grid[J].Journal of Space Weather and Space Climate,2014,4:A09.
[13]Viljanen A,Pirjola R.Influence of spatial variations of the geoelectric field on geomagnetically induced currents[J].Journal of Space Weather and Space Climate,2017,7:A22.
[14]Love J J,Rigler E J,Pulkkinen A,et al.On the lognormality of historical magnetic storm intensity statistics:Implications for extreme-event probabilities[J].Geophysical Research Letters,2015,42(16):6544-6553.
[15]Danskin D W,Lotz S I.Analysis of geomagnetic hourly ranges[J].Space Weather,2015,13(8):458-468.
[16]Lotz S I,Danskin D W.Extreme value analysis of induced geoelectric field in South Africa[J].Space Weather,2017,15(10):1347-1356.
[17]Pulkkinen A,Pirjola R,Viljanen A.Statistics of extreme geomagnetically induced current events[J].Space Weather,2008,6(7):S07001.
[18]Pulkkinen A,Bernabeu E,Eichner J,et al.Generation of100-year geomagnetically induced current scenarios[J].Space Weather,2012,10(4):S04003.
[19]Barbosa C S,Caraballo R,Alves L R,et al.The Tsallis statistical distribution applied to geomagnetically induced currents[J].Space Weather,2017,15(9):1094-1101.
[20]刘连光,吴伟丽.磁暴影响电力系统安全风险评估思路与理论框架[J].中国电机工程学报,2014,34(10):1583-1591.Liu Lianguang,Wu Weili.Security risk assessment ideas and theoretical framework for power system considering geomagnetic storm[J].Proceedings of the CSEE,2014,34(10):1583-1591(in Chinese).