计及冲击风险及分布熵的电网连锁故障预测
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摘要
电网连锁故障预测有利于预防大停电事故的发生。为了弥补现有电网连锁故障预测中未计及线路故障退出运行后系统均匀性的不足,提出了计及电网故障过程中的冲击风险及故障后电网均匀状态的电网连锁故障预测方法。考虑节点关联度,引入电压波动熵的概念,用以准确描述关键线路退出后电网的电压波动情况;运用熵理论,对断线后电网电压分布和有功分布进行分析,克服了以往连锁故障预测未计及电网均匀性的缺陷。采用离差最大化灰色关联,综合考虑线路自身重要性、冲击风险指标以及分布熵指标。通过RTS-79系统仿真,得出了风险值较高的连锁故障链,结果证明该模型实际有效。
Grid cascading failure prediction is conducive to preventing the occurrence of blackouts. In order to make up for the lack of uniformity of the system after the failure of the line faults in the existing grid cascading failure prediction, a grid cascading failure prediction method that takes into account the impact risk during the grid fault and the uniform state of the grid after the fault is proposed. Considering the degree of node correlation, the concept of voltage fluctuation entropy is introduced to accurately describe the voltage fluctuation of the grid after the exit of the critical line. The entropy theory is used to analyze the voltage distribution and active distribution of the grid after the disconnection, which overcomes the previous cascading failure prediction. Taking into account the defects of grid uniformity, the gray correlation is maximized by dispersion, and the importance of the line itself, the impact risk index and the distribution entropy index are comprehensively considered. Through the RTS-79 system simulation, the chain of fault chains with higher risk value is obtained. The result proves that the model is practically effective.
Grid cascading failure prediction is conducive to preventing the occurrence of blackouts. In order to make up for the lack of uniformity of the system after the failure of the line faults in the existing grid cascading failure prediction, a grid cascading failure prediction method that takes into account the impact risk during the grid fault and the uniform state of the grid after the fault is proposed. Considering the degree of node correlation, the concept of voltage fluctuation entropy is introduced to accurately describe the voltage fluctuation of the grid after the exit of the critical line. The entropy theory is used to analyze the voltage distribution and active distribution of the grid after the disconnection, which overcomes the previous cascading failure prediction. Taking into account the defects of grid uniformity, the gray correlation is maximized by dispersion, and the importance of the line itself, the impact risk index and the distribution entropy index are comprehensively considered. Through the RTS-79 system simulation, the chain of fault chains with higher risk value is obtained. The result proves that the model is practically effective.
引文
[1]程林,刘满君,易俊,等.基于运行可靠性模型的连锁故障模拟及薄弱环节分析[J].电网技术,2016,40(5):1488-1494.
[2]丁明,钱宇骋,张晶晶.考虑多时间尺度的连锁故障演化和风险评估模型[J].中国电机工程学报,2017,37(20):5902-5912.
[3]胡萍,梅挺,范文礼.复杂电网连锁故障预测研究综述[J].中国科学:技术科学,2017,47(4):355-363.
[4]杨嘉湜,黄林,刘捷,等.基于元胞自动机的电力信息物理系统连锁故障仿真分析[J].电工电能新技术,2018,37(9):33-41.
[5]王佳明,刘文颖,张建立.恶劣天气下的复杂电网连锁故障在线预警[J].电网技术,2012,36(5):239-244.
[6]I.DOBSON,B.A.CARRERAS,D.E.NEWMAN.Branching process models for the exponentially increasing portions of cascading failure blackout-s[C].System Sciences 2005.HICSS '05.Proceedings of the 38th Annual Hawaii International Conference on,2005.
[7]J.QI,S.MEI.Blackout model considering slow process and SOC analysis[C].2012 IEEE Power and Energy Society General Meeting,San Diego,CA,2012.
[8]李辉,贾晓风,李利娟,等.基于元胞自动机的电网隐性故障传播模型关键线路识别方法[J].电力系统保护与控制,2018,46(6):16-23.
[9]潘一飞,李华强,贺含峰,等.小世界网络下电网连锁故障预测[J].电力系统及其自动化学报,2013,25(2):148-153.
[10]张娟,童晓阳,姜建伟.基于点渗流和熵权法的连锁故障路径风险评估[J].电力系统及其自动化学报,2018,30(2):20-25.
[11]刘文颖,杨楠,张建立,等.计及恶劣天气因素的复杂电网连锁故障事故链模型[J].中国电机工程学报,2012,32(7):53-59.
[12]孙伟卿,王承民,曾平良,等.电力系统均匀性评价方法与指标综述[J].电网技术,2015,39(5):1205-1212.
[13]贺强,李华强,郑国,等.基于运行可靠性和结构重要度的连锁故障预测[J].电测与仪表,2015,52(1):47-52.
[14]曾磊磊,曾鑫,吕嘉.考虑网络结构和运行状态的电网脆弱线路辨识[J].智慧电力,2018,46(8):8-12.
[15]杨植雅,李华强,黄文婧,等.考虑电网运行状态和结构关联的连锁故障序列预测[J].电力建设,2017,38(11):73-80.
[16]丁少倩,林涛,徐遐龄,等.基于负荷转移系数的电气介数在电网结构脆弱性评估方法中的应用[J].电测与仪表,2016,53(18):6-9.
[17]徐岩,郅静.基于改进电气介数的关键线路辨识[J].华北电力大学学报(自然科学版),2015,42(6):24-28.
[18]王涛,王兴武,顾雪平,等.基于概率及结构重要度的电力系统事故链模型与仿真[J].电力自动化设备,2013,33(7):51-56.
[2]丁明,钱宇骋,张晶晶.考虑多时间尺度的连锁故障演化和风险评估模型[J].中国电机工程学报,2017,37(20):5902-5912.
[3]胡萍,梅挺,范文礼.复杂电网连锁故障预测研究综述[J].中国科学:技术科学,2017,47(4):355-363.
[4]杨嘉湜,黄林,刘捷,等.基于元胞自动机的电力信息物理系统连锁故障仿真分析[J].电工电能新技术,2018,37(9):33-41.
[5]王佳明,刘文颖,张建立.恶劣天气下的复杂电网连锁故障在线预警[J].电网技术,2012,36(5):239-244.
[6]I.DOBSON,B.A.CARRERAS,D.E.NEWMAN.Branching process models for the exponentially increasing portions of cascading failure blackout-s[C].System Sciences 2005.HICSS '05.Proceedings of the 38th Annual Hawaii International Conference on,2005.
[7]J.QI,S.MEI.Blackout model considering slow process and SOC analysis[C].2012 IEEE Power and Energy Society General Meeting,San Diego,CA,2012.
[8]李辉,贾晓风,李利娟,等.基于元胞自动机的电网隐性故障传播模型关键线路识别方法[J].电力系统保护与控制,2018,46(6):16-23.
[9]潘一飞,李华强,贺含峰,等.小世界网络下电网连锁故障预测[J].电力系统及其自动化学报,2013,25(2):148-153.
[10]张娟,童晓阳,姜建伟.基于点渗流和熵权法的连锁故障路径风险评估[J].电力系统及其自动化学报,2018,30(2):20-25.
[11]刘文颖,杨楠,张建立,等.计及恶劣天气因素的复杂电网连锁故障事故链模型[J].中国电机工程学报,2012,32(7):53-59.
[12]孙伟卿,王承民,曾平良,等.电力系统均匀性评价方法与指标综述[J].电网技术,2015,39(5):1205-1212.
[13]贺强,李华强,郑国,等.基于运行可靠性和结构重要度的连锁故障预测[J].电测与仪表,2015,52(1):47-52.
[14]曾磊磊,曾鑫,吕嘉.考虑网络结构和运行状态的电网脆弱线路辨识[J].智慧电力,2018,46(8):8-12.
[15]杨植雅,李华强,黄文婧,等.考虑电网运行状态和结构关联的连锁故障序列预测[J].电力建设,2017,38(11):73-80.
[16]丁少倩,林涛,徐遐龄,等.基于负荷转移系数的电气介数在电网结构脆弱性评估方法中的应用[J].电测与仪表,2016,53(18):6-9.
[17]徐岩,郅静.基于改进电气介数的关键线路辨识[J].华北电力大学学报(自然科学版),2015,42(6):24-28.
[18]王涛,王兴武,顾雪平,等.基于概率及结构重要度的电力系统事故链模型与仿真[J].电力自动化设备,2013,33(7):51-56.