山东大学学报 (工学版) ›› 2022, Vol. 52 ›› Issue (6): 157-166.doi: 10.6040/j.issn.1672-3961.0.2022.209
• 电气工程 • 上一篇
于群1,肖松青1*,曹娜1,何剑2,张建新3
YU Qun1, XIAO Songqing1*, CAO Na1, HE Jian2, ZHANG Jianxin3
摘要: 在已有的极值模型的基础上,利用超阈值(peaks over threshold, POT)提出基于相对值法的POT-CVaRBootstrap模型,并对中国电网停电损失风险进行评估。结合电网装机容量的发展趋势,对比利用绝对值法与相对值法统计的停电损失负荷数据,表明相对值预测更符合未来电网损失;基于相对值数据建立POT模型,提出W2& A2-Hill图的阈值选取方法。为了解决电网停电损失负荷样本数量稀少的问题,结合对有限样本重复抽样的Bootstrap法,建立CVaRBootstrap停电损失风险评估模型,利用中国电网停电损失负荷数据验证了模型的有效性,得出CVaRBootstrap模型的评估结果更优,在此基础上给出我国未来10 a的停电事故风险评估,未来很长一段时间我国的停电损失负荷将仍呈现增长趋势,且华北、华东和南方地区是停电事故发生较严重的地区。
中图分类号:
[1] 汤涌,卜广全,易俊.印度“7.30”、“7.31”大停电事故分析及启示[J]. 中国电机工程学报,2012,32(25):167-174. TANG Yong, BU Guangquan, YI Jun. Analysis and enlightenment of "7.30" and "7.31" blackouts in India[J]. Chinese Journal of electrical engineering, 2012, 32(25):167-174. [2] 邵瑶,汤涌,易俊,等.土耳其“3·31”大停电事故分析及启示[J].电力系统自动化,2016,40(23):9-14. SHAO Yao, TANG Yong, YI Jun, et al. Analysis and enlightenment of "March 31" blackout in Turkey[J]. Power system automation, 2016, 40(23):9-14. [3] 林伟芳,易俊,郭强,等.阿根廷“6.16”大停电事故分析及对中国电网的启示[J].中国电机工程学报,2020,40(9):2835-2842. LIN Weifang, YI Jun, GUO Qiang, et al. Analysis of “6.16” blackout in argentina and its enlightenment to China's power grid[J]. Chinese Journal of electrical engineering, 2020, 40(9):2835-2842. [4] 孙传文.“12.28”墨西哥大停电事故的分析及其对我国电网运行的启示及建议[J].电气时代,2021(9):44-46. SUN Chuanwen. Analysis of “12.28” blackout in Mexico and its enlightenment and suggestions for China's power grid operation [J]. Electrical Age, 2021(9):44-46. [5] 安学民,孙华东,张晓涵,等.美国得州“2.15”停电事件分析及启示[J]. 中国电机工程学报, 2021, 41(10): 3407-3415. AN Xuemin, SUN Huadong, ZHANG Xiaohan, et al. Analysis and enlightenment of “2.15” power outage in Texas[J]. Chinese Journal of Electrical Engineering, 2021, 41(10):3407-3415. [6] BEIRLANT J, TEUGELS J L, VYNCKIE P. Practical analysis of extreme values[D]. Leuven, Belgium:Leuven University Press, 1996:1-9. [7] KINNISON R R. Applied extreme value statistics[M]. Macmillan, Columbus: Battelle Press, 1985:1-3. [8] BEIRLANT J, TEUGELS J L, GOEGEBEUR Y, et al. Statistics of extremes: theory and applications[M]. New York, USA:Wiley, 2004:2-15. [9] KOTZ S, NADARAJAH S. Extreme value distributions: theory and applications[D]. London:Imperial College Press, 2000:7-23. [10] PAN J, CHENG S H. Asymptotic expansion for distribution function of moment estimator for the extreme-value index[J]. Science in China(Series A), 2000, 43(11):1131-1143. [11] 王旭,史道济.极值统计理论在金融风险中的应用[J].数量经济技术经济研究,2001,11(8):109-111. WANG Xu, SHI Daoji. Application of extreme value statistical theory in financial risk[J]. Quantitative Economy, Technical Economy Research, 2001, 11(8):109-111. [12] 陈兴旺.广义极值分布理论在重现期计算的应用[J].气象与减灾研究,2008,31(4):52-54. CHEN Xingwang. Application of generalized extreme value distribution theory in return period calculation[J]. Research on Meteorology and Disaster Reduction, 2008, 31(4):52-54. [13] 鲁帆,严登华.基于广义极值分布和Metropolis-Hastings抽样算法的贝叶斯MCMC洪水频率分析方法[J].水力学报,2013,44(8):942-949. LU fan, YAN Denghua. Bayesian MCMC flood fre-quency analysis method based on generalized extreme value distribution and Metropolis Hastings sampling algorithm[J]. Journal of Hydraulics, 2013, 44(8):942-949. [14] 钱小仕,王福昌,曹桂荣,等.广义极值分布在地震危险性分析中的应用[J].地震研究,2012,35(1): 73-77. QIAN Xiaoshi, WANG Fuchang, CAO Guirong, et al. Application of generalized extreme value distribution in seismic risk analysis[J]. Seismic Research, 2012, 35(1):73-77. [15] 于群,郭剑波.电网停电事故的自组织临界性及其极值分析[J].电力系统自动化,2007,31(3):1-3. YU Qun, GUO Jianbo. Self organized criticality of power grid outage and its mechanism analysis[J]. Power System Automation, 2007, 31(3):1-3. [16] 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[J].电力系统自动化,2016,40(8):71-77. YU Qun, SHI Liang, CAO Na, et al. Application of generalized extreme value theory in load loss prediction of blackout[J]. Power System Automation, 2016, 40(8):71-77. [17] 杨学敏.基于VaR模型的互联网金融收益风险度量研究[D].北京:对外经济贸易大学,2018. YANG Xuemin. Research on Internet financial return risk measurement based on VAR model[D].Beijing: University of International Business and Economics, 2018. [18] 张昱城,葛林洁,李延军.股票流动性对股市尾部风险的影响:基于POT模型的实证研究[J].东北大学学报(社会科学版),2021,23(2):21-28. ZHANG Yucheng, GE Linjie, LI Yanjun. The impact of stock liquidity on stock market tail risk: an empirical study based on pot model[J]. Journal of Northeast University(Social Science Edition), 2021, 23(2):21-28. [19] 巢文,邹辉文.基于POT模型的巨灾损失VaR和CVaR估计[J].北京化工大学学报(社会科学版),2020(2):18-22. CHAO Wen, ZOU Huiwen. Estimation of catastrophe loss VaR and CVaR based on pot model[J]. Journal of Beijing University of Chemical Technology(Social Science Edition), 2020(2): 18-22. [20] 张文华.面向系统灵活性的高比例可再生能源电力规划研究[D].北京:华北电力大学(北京),2021. ZHANG Wenhua. Research on high proportion renewable energy power planning for system flexibility[D]. Beijing: North China Electric Power University(Beijing), 2021. [21] 国家电力调度通信中心.全国电网典型事故分析:1988—1998[M].北京:中国电力出版社,2000. [22] 国家电力调度通信中心.全国电网典型事故分析:1999—2007[M].北京:中国电力出版社,2008. [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[M].北京:中国电力出版社,2009. [24] 《中国电力年鉴》编辑委员会.中国电力统计年鉴[M].北京:中国电力出版社,2020. [25] 于群,石良,郭剑波,等.基于相对值法的区域电网停电事故自组织特性分析[J].中国电力,2016,49(1):91-95. YU Qun, SHI Liang, GUO Jianbo, et al. Analysis of self-organization characteristics of regional power grid outage based on relative value method[J]. China Power, 2016, 49(1):91-95. [26] 石良.基于广义极值理论的电网风险分级及预警技术研究[D]. 青岛:山东科技大学,2016. SHI Liang. Research on power grid risk classification and early warning technology based on generalized extreme value theory[D]. Qingdao: Shandong University of Science and Technology, 2016. [27] 吴亚玲,姜珊,吴先华,等.基于极值理论的广东省台风灾害损失分布及其金融对策研究[J].灾害学,2017,32(1):126-131. WU Yaling, JIANG Shan, WU Xianhua, et al. Study on typhoon disaster loss distribution and financial countermeasures in Guangdong Province based on extreme value theory[J]. Disaster Science, 2017, 32(1):126-131. [28] BORTKIEWICZ L. Variations breite and mittlerer fehler[J]. Sitzungsber Berlin Mathematical Gesellschaft, 1922, 21: 3-11. [29] 王皓.极值理论在测度中国股市VaR中的应用与比较[D].杭州:浙江大学,2008. WANG Hao. Application and comparison of extreme value theory in measuring VaR of China's stock market[D]. Hangzhou: Zhejiang University, 2008. [30] 詹原瑞,田宏伟.极值理论(EVT)在汇率受险价值(VaR)计算中的应用[J].系统工程学报,2000, 15(1):44-53. ZHAN Yuanrui, TIAN Hongwei. Application of extreme value theory(EVT)in the calculation of exchange rate VaR[J]. Journal of Systems Engineering, 2000, 15(1): 44-53. [31] 刘良.基于极值理论的人民币汇率风险测度[D].南昌:江西财经大学,2017. LIU Liang. RMB exchange rate risk measurement based on extreme value theory[D]. Nanchang: Jiangxi University of Finance and Economics, 2017. [32] 吴亮,邓明.基于广义帕累托分布稳健估计法的沪市VaR预测[J].首都经济贸易大学学报,2013,15(4):35-43. WU Liang, DENG Ming. VaR prediction of Shanghai stock market based on generalized Pareto distribution robust estimation method[J]. Journal of Capital University of Economics and Trade, 2013, 15(4): 35-43. [33] 刘义艳,于太珊.基于滑块自助法与长短时记忆网络的电力负荷区间预测研究[J].电气自动化,2022,44(1):70-73. LIU Yiyan, YU Taishan. Research on power load interval forecasting based on sliding block self-help method and long-term and short-term memory network[J]. Electrical Automation, 2022, 44(1):70-73. [34] KUPIEC P H. Techniques for verifying the accuracy of risk measurement models[J]. Journal of Derivatives, 1995, 3(2): 73-84. [35] 鲁宗相,黄瀚.高比例可再生能源电力系统结构形态演化及电力预测展望[J].电力系统自动化,2017,41(9):12-18. LU Zongxiang, HUANG Han. Structural evolution and power forecasting prospect of high proportion renewable energy power system[J]. Power System Automation, 2017, 41(9): 12-18. |
[1] | 闵海根,方煜坤,吴霞,王武祺. 网联交通环境下的车-车通信故障诊断方法[J]. 山东大学学报 (工学版), 2021, 51(6): 84-92. |
[2] | 成科扬,孙爽,詹永照. 基于背景复杂度自适应距离阈值的修正SuBSENSE算法[J]. 山东大学学报 (工学版), 2020, 50(3): 38-44. |
[3] | 李广丽,刘斌,朱涛,殷依,张红斌. 基于优选典型相关分量的跨媒体检索模型[J]. 山东大学学报 (工学版), 2018, 48(5): 38-46. |
[4] | 王海军,葛红娟,张圣燕. 基于L1范数和最小软阈值均方的目标跟踪算法[J]. 山东大学学报(工学版), 2016, 46(3): 14-22. |
[5] | 花景新, 薄煜明, 陈志敏. 基于改进粒子群优化神经网络的房地产市场预测[J]. 山东大学学报(工学版), 2014, 44(4): 22-30. |
[6] | 翟东海1,2,鱼江1,聂洪玉1,崔静静1,杜佳1. 基于相关性反馈的自适应热点话题追踪模型[J]. 山东大学学报(工学版), 2014, 44(1): 7-12. |
[7] | 牟世刚,冯显英*,晏志文,杨静芳. 基于小波分析的动平衡机不平衡量提取方法研究[J]. 山东大学学报(工学版), 2011, 41(3): 62-66. |
[8] | 胡晓庆1,马儒宁1*,钟宝江2. 层次聚类算法的有效性研究[J]. 山东大学学报(工学版), 2010, 40(5): 146-149. |
[9] | 刘成云 陈振学 常发亮. 基于平稳小波的自适应阈值MR图像去噪法[J]. 山东大学学报(工学版), 2009, 39(5): 58-61. |
[10] | 吴师岗. 相变对ZrO2/SiO2多层膜激光损伤阈值的影响[J]. 山东大学学报(工学版), 2009, 39(1): 114-117. |
[11] | 黄雪菊,郭举修,武颖静 . 图像边缘检测的小波包分解算法[J]. 山东大学学报(工学版), 2007, 37(5): 123-126 . |
[12] | 陈文钢 ,田岚,姜晓庆,孙英明 . 一种噪声谱快速跟踪的语音增强方法[J]. 山东大学学报(工学版), 2006, 36(4): 26-28 . |
[13] | 李秀红,张东升 . (α,β)-粗糙集模型中阈值的确定与解释[J]. 山东大学学报(工学版), 2006, 36(2): 81-85 . |
|