基于改进负载潮流熵指标准确辨识电网脆性支路的方法
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摘要
电力系统关键环节定位是电网安全分析的核心问题。针对基于潮流状态识别脆性支路只考虑系统静态特性,存在忽略系统运行极限及元件本身特性影响的不足,以及基于电网复杂拓扑结构分析辨识脆性支路时忽略电压运行状态影响,容易引起漏选的缺陷,提出一套改进负载潮流熵权指标准确辨识电网脆性支路的方法,由2阶段3类排序筛选构成,初筛阶段提出负载潮流熵和支路开断熵测度两指标,能准确评估电网稳态时支路不稳定运行特征,以及电网受扰后系统维持稳定运行的趋势。深筛阶段提出含调节因子的双测度熵和加权综合熵指标,满足电网设计或运行等不同场景对辨识脆性支路的需求。针对所提辨识方法,选经典IEEE10机39节点算例,并与其他方法开展对比实验,表明所提方法能更全面、更准确辨识电网脆性支路的优点。
Critical link location of power system is the key issue of power grid security analysis. For the brittle branches based on load flow state, only the static characteristics of the system are considered. There are deficiencies in ignoring the system operating limit and the characteristics of the components themselves. And also, the influence of voltage running state is neglected when the brittle branches areidentified based on complex topology analysis of the power grid. All of above reasons are prone to causing choice missing. In the paper, a set of improved load flow entropy indexes is proposed to accurately identify the brittle branches of power grid. It consists of two stages and three types of sorting and screening. In the initial screening stage, two indexes of improved load flow entropy and branch outage entropy measure are proposed to more accurately describe the trend of stable operation of the system after disturbance. In the deep screening stage, a weighted comprehensive entropy index with adjustment factor and double measure entropy sum is proposed. It meets the need of identifying brittle branches in different scenarios such as power grid design or operation. The classic IEEE 10 machine 39-node example is used and compared with other methods. Simulation results show that the proposed method can identify the brittle branches of the power grid more comprehensively and accurately.
Critical link location of power system is the key issue of power grid security analysis. For the brittle branches based on load flow state, only the static characteristics of the system are considered. There are deficiencies in ignoring the system operating limit and the characteristics of the components themselves. And also, the influence of voltage running state is neglected when the brittle branches areidentified based on complex topology analysis of the power grid. All of above reasons are prone to causing choice missing. In the paper, a set of improved load flow entropy indexes is proposed to accurately identify the brittle branches of power grid. It consists of two stages and three types of sorting and screening. In the initial screening stage, two indexes of improved load flow entropy and branch outage entropy measure are proposed to more accurately describe the trend of stable operation of the system after disturbance. In the deep screening stage, a weighted comprehensive entropy index with adjustment factor and double measure entropy sum is proposed. It meets the need of identifying brittle branches in different scenarios such as power grid design or operation. The classic IEEE 10 machine 39-node example is used and compared with other methods. Simulation results show that the proposed method can identify the brittle branches of the power grid more comprehensively and accurately.
引文
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[17]丁明,韩平平.基于小世界拓扑模型的大型电网脆弱性评估算法[J].电力系统自动化,2006,30(8):7-10,40.Ding Ming,Han Pingping.Small-world topological model based vulnerability assessment algorithm for large-scale power grid[J].Automation of Electric Power Systems,2006,30(8):7-10,40(in Chinese).
[18]丁明,韩平平.加权拓扑模型下的小世界电网脆弱性评估[J].中国电机工程学报,2008,28(10):20-25.Ding Ming,Han Pingping.Vulnerability assessment to small-world power grid based on weighted topological model[J].Proceedings of the CSEE,2008,28(10):20-25(in Chinese).
[19]刘小丽,毛弋,梁杉,等.基于综合介数的电网脆弱支路辨识[J].电力系统保护与控制,2016,44(2):116-121.Liu Xiaoli,Mao Yi,Liang Shan,et al.Identification of vulnerable lines in power grid based on comprehensive betweenness index[J],Power System Protection and Control,2016,44(2):116-121(in Chinese).
[20]张才斌,游昊,李本瑜.计及拓扑结构和运行状态的支路重要度评估方法[J].电力系统自动化,2017,41(7):15-20.Zhang Caibin,You Hao,Li Benyu,et al.Assessment method of branch importance considering topological structure and operation state[J].Automation of Electric Power Systems,2017,41(7):15-20(in Chinese).
[21]哈肯.高等协同学[M].郭治安,译.北京:科学出版社,1989.
[22]荣盘祥,王继尧,金鸿章.复杂系统的脆性与系统演化分析[J].电机与控制学报,2004,8(2):142-144,201.Rong Panxiang,Wang Jiyao,Jin Hongzhang.The analysis of system evolvement based on complex system brittleness[J].Electric Machines And Control,2004,8(2):142-144,201(in Chinese).
[23]宋墩文.基于多源信息融合的电网暂态稳定风险评估[D].北京:中国农业大学,2016.
[24]杨林涛,杨洪耕,刘亚磊.基于联络线簇能量传输模式的互联区域电网脆弱性评估[J].工程科学与技术,2017,49(6):142-148.Yang Lintao,Yang Honggeng,Liu Yalei.Vulnerability evaluation of district power grid based on tie-line groups energy transmission mode[J].Advanced Engineering Sciences,2017,49(6):142-148(in Chinese).
[25]李丽华.基于线路指标熵识别电网脆弱环节的研究[D].北京:华北电力大学,2018.
[26]徐政.柔性直流输电系统[M].北京:机械工业出版社,2014:6.
[27]徐岩,郅静.基于加权潮流熵的电网故障传播脆弱线路识别[J].现代电力,2016,33(3):88-94.Xu Yan,Zhi Jing.Identification of vulnerable lines for fault propagation in power grid based on the weighted power flow entropy[J],Modern Electric Power,2016,33(3):88-94(in Chinese).
[28]蔡晔,曹一家,李勇,等.考虑电压等级和运行状态的电网脆弱线路辨识[J].中国电机工程学报,2014,34(13):2124-2131.Cai Ye,Cao Yijia,Li Yong,et al.Identification of vulnerable lines in urban power grid based on voltage grade and running state[J],Proceedings of the CSEE,2014,34(13):2124-2131(in Chinese).
[2]高翔,庄侃沁,孙勇.西欧电网“11.4”大停电事故的启示[J].电网技术,2007,31(1):25-31.Gao Xiang,Zhuang Kanqin,Sun Yong.Lessons and enlightenment from blackout occurred in UCTE grid on November 4,2006[J].Power System Technology,2007,31(1):25-31(in Chinese).
[3]Guo Chena,Zhao Yangdong,Hill D J.Attack structural vulnerability of power grids:a hybrid approach based on complex networks[J].Physica A,2010,389(3):595-603.
[4]沈瑞寒,刘涤尘,赵洁,等.基于加权网络模型的电网潮流转移下危险线路识别[J].电网技术,2012,36(5):245-250.Shen Ruihan,Liu Dichen,Zhao Jie,et al.Weighted network model based recognition of dangerous lines under power flow transferring[J].Power System Technology,2012,36(5):245-250(in Chinese).
[5]刘文颖,王佳明,谢昶,等.基于脆性风险熵的复杂电网连锁故障脆性源辨识模型[J].中国电机工程学报,2012,32(31):142-149.Liu Wenying,Wang Jiaming,Xie Chang.Brittleness source identification model for cascading failure of complex power grid based on brittle risk entropy[J].Proceedings of the CSEE,2012,32(31):142-149(in Chinese).
[6]曾珂,李华强,曾梦婕,等.考虑改进潮流冲击熵的电力系统融冰预防控制[J].电网技术,2015,39(2):582-586.Zeng Ke,Li Huaqiang,Zeng Mengjie,et al.Power system ice-melting preventive control considering improved transfer entropy of power flow[J].Power System Technology,2015,39(2):582-586(in Chinese).
[7]张娟,童晓阳,姜建伟.基于渗流和风险理论的电力系统连锁故障分析[J].电力系统自动化,2017,41(5):46-52.Zhang Juan,Tong Xiaoyang,Jiang Jianwei.Analysis on power system cascading failure based on percolation and risk theory[J].Automation of Electric Power Systems,2017,41(5):46-52(in Chinese).
[8]王涛,高成彬,顾雪平,等.基于功率介数的电网关键环节辨识[J].电网技术,2014,38(7):1907-1913.Wang Tao,Gao Chengbin,Gu Xueping,et al.Power betweenness based identification of power grid critical links[J].Power System Technology,2014,38(7):1907-1913(in Chinese).
[9]何俊,庞松龄,禹冰,等.基于容量介数指标的电网脆弱支路识别[J].电力系统保护与控制,2013,41(8):30-35.He Jun,Pang Songling,Yu Bing,et al.Vulnerable line identification of power grid based on capacity betweenness index[J].Power System Protection and Control,2013,41(8):30-35(in Chinese).
[10]王仁伟,张友刚,杨阳,等.基于电气介数的复杂电网脆弱线路辨识[J].电力系统保护与控制,2014,42(20):1-6.Wang Renwei,Zhang Yougang,Yang Yang,et al.Vulnerable line identification of complex power grid based on electrical betweenness[J].Power System Protection and Control,2014,42(20):1-6(in Chinese).
[11]李勇,刘俊勇,刘晓宇,等.基于潮流熵测度的连锁故障脆弱支路评估及其在四川主干电网中的应用[J].电力自动化设备,2013,33(10):40-46.Li Yong,Liu Junyong,Liu Xiaoyu,et al.Vulnerability assessment based on power flow entropy for lines in cascading failures and its application in Sichuan backbone power grid[J].Electric Power Automation Equipment,2013,33(10):40-46(in Chinese).
[12]丁明,过弈,张晶晶.基于效用风险熵的复杂电网连锁故障脆弱性辨识[J].电力系统自动化,2013,37(17):52-57.Ding Ming,Guo Yi,Zhang Jingjing.Vulnerability identification for cascading failures of complex power grid based on effect risk entropy[J].Automation Of Electric Power Systems,2013,37(17):52-57(in Chinese).
[13]张弘历,李华强,杨植雅,等.基于潮流增长率泰尔熵的脆弱支路辨识[J].电网技术,2017,41(7):2340-2346.Zhang Hongli,Li Huaqiang,Yang Zhiya,et al.Identification of vulnerable line based on the theil entropy of flow growth rate[J].Power System Technology,2017,41(7):2340-2346(in Chinese).
[14]吕歆瑶,李华强,郑国,等.基于综合脆性关联度的连锁故障预测与冲击辨识[J].电力自动化设备,2015,35(12):116-125.LüXinyao,Li Hhuaqiang,Zheng Guo,et al.Cascading failure forecast and impact identification based on comprehensive brittleness relevance[J].Electric Power Automation Equipment,2015,35(12):116-125(in Chinese).
[15]陈晓刚,孙可,曹一家.基于复杂网络理论的大电网结构脆弱性分析[J].电工技术学报,2007,22(10):138-144.Chen Xiaogang,Sun Ke,Cao Yijia.Structural vulnerability analysis of large power grid based on complex network theory[J].Transactions of China Electrotechnical Society,2007,22(10):138-144(in Chinese).
[16]肖盛,张建华.基于小世界拓扑模型的电网脆弱性评估[J].电网技术,2010,34(8):64-68.Xiao Sheng,Zhang Jianhua.Assessment of power grid vulnerability based on small-world topological model[J].Power System Technology,2010,34(8):64-68(in Chinese).
[17]丁明,韩平平.基于小世界拓扑模型的大型电网脆弱性评估算法[J].电力系统自动化,2006,30(8):7-10,40.Ding Ming,Han Pingping.Small-world topological model based vulnerability assessment algorithm for large-scale power grid[J].Automation of Electric Power Systems,2006,30(8):7-10,40(in Chinese).
[18]丁明,韩平平.加权拓扑模型下的小世界电网脆弱性评估[J].中国电机工程学报,2008,28(10):20-25.Ding Ming,Han Pingping.Vulnerability assessment to small-world power grid based on weighted topological model[J].Proceedings of the CSEE,2008,28(10):20-25(in Chinese).
[19]刘小丽,毛弋,梁杉,等.基于综合介数的电网脆弱支路辨识[J].电力系统保护与控制,2016,44(2):116-121.Liu Xiaoli,Mao Yi,Liang Shan,et al.Identification of vulnerable lines in power grid based on comprehensive betweenness index[J],Power System Protection and Control,2016,44(2):116-121(in Chinese).
[20]张才斌,游昊,李本瑜.计及拓扑结构和运行状态的支路重要度评估方法[J].电力系统自动化,2017,41(7):15-20.Zhang Caibin,You Hao,Li Benyu,et al.Assessment method of branch importance considering topological structure and operation state[J].Automation of Electric Power Systems,2017,41(7):15-20(in Chinese).
[21]哈肯.高等协同学[M].郭治安,译.北京:科学出版社,1989.
[22]荣盘祥,王继尧,金鸿章.复杂系统的脆性与系统演化分析[J].电机与控制学报,2004,8(2):142-144,201.Rong Panxiang,Wang Jiyao,Jin Hongzhang.The analysis of system evolvement based on complex system brittleness[J].Electric Machines And Control,2004,8(2):142-144,201(in Chinese).
[23]宋墩文.基于多源信息融合的电网暂态稳定风险评估[D].北京:中国农业大学,2016.
[24]杨林涛,杨洪耕,刘亚磊.基于联络线簇能量传输模式的互联区域电网脆弱性评估[J].工程科学与技术,2017,49(6):142-148.Yang Lintao,Yang Honggeng,Liu Yalei.Vulnerability evaluation of district power grid based on tie-line groups energy transmission mode[J].Advanced Engineering Sciences,2017,49(6):142-148(in Chinese).
[25]李丽华.基于线路指标熵识别电网脆弱环节的研究[D].北京:华北电力大学,2018.
[26]徐政.柔性直流输电系统[M].北京:机械工业出版社,2014:6.
[27]徐岩,郅静.基于加权潮流熵的电网故障传播脆弱线路识别[J].现代电力,2016,33(3):88-94.Xu Yan,Zhi Jing.Identification of vulnerable lines for fault propagation in power grid based on the weighted power flow entropy[J],Modern Electric Power,2016,33(3):88-94(in Chinese).
[28]蔡晔,曹一家,李勇,等.考虑电压等级和运行状态的电网脆弱线路辨识[J].中国电机工程学报,2014,34(13):2124-2131.Cai Ye,Cao Yijia,Li Yong,et al.Identification of vulnerable lines in urban power grid based on voltage grade and running state[J],Proceedings of the CSEE,2014,34(13):2124-2131(in Chinese).