基于复杂网络的电网关键单元辨识评估在应急管理体系中的应用
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摘要
电网由于自身设备数量、种类繁多,网架结构错综复杂,其安全稳定运行经常会受到复杂外部环境影响。基于复杂网络理论,采用电网关键单元辨识评估方法,根据电网的电能传输物理特性,对电网中的节点及线路进行结构重要度排序,辨识评估电网中的关键结构单元,可量化评估电网运行风险,制定切实有效的预防控制措施,预防减少电网应急事故的发生,降低电网运行风险。
Power grid structure is complex because of the number and variety of its own equipment, so the safe and stable operation is often affected by complex external environment. At present, the main method of making the power grid risk assessment is to monitor the sttatus information of the power grid continuously, to evaluate the risk by synthesizing the preset risk assessment index, and to determine the risk level. Based on complex network theory, this paper adopts the method of identification and evaluation of key units in the power grid. According to the physical characteristics of electric power transmission, the nodes and lines in the power grid are ranked by their structural importance, and the key structural units in the power grid are identified and evaluated, preventing the occurrence of the power grid emergency accidents and reducing the risk of the power grid operation.
Power grid structure is complex because of the number and variety of its own equipment, so the safe and stable operation is often affected by complex external environment. At present, the main method of making the power grid risk assessment is to monitor the sttatus information of the power grid continuously, to evaluate the risk by synthesizing the preset risk assessment index, and to determine the risk level. Based on complex network theory, this paper adopts the method of identification and evaluation of key units in the power grid. According to the physical characteristics of electric power transmission, the nodes and lines in the power grid are ranked by their structural importance, and the key structural units in the power grid are identified and evaluated, preventing the occurrence of the power grid emergency accidents and reducing the risk of the power grid operation.
引文
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[18]张涛,孙晓伟,徐雪琴等.基于有功潮流介数的电网关键线路辨识[J].电网技术,2016,40(1):193-198.ZHANG Tao, SUN Xiaowei, XU Xueqin et al. Identification of critical lines in power grid based on active power flow betweenness[J]. Power Grid Technology, 2016, 40(1):193-198.
[2]闫瑜,周勤勇,贺海磊等.基于复杂网络理论的电网分区及断面搜索方法[J].电力建设,2017(6):100-107.YAN Yu,ZHOU Qinyong,HE Hailei,et al. Subarea Division and Transmission Sections Search Method Based on Complex Network Theory[J]. Power Construction, 2017(6):100-107.
[3]王靖飞.基于复杂网络的风电消纳能力评估模型改进[J].中国电力,2017(1):136-139,145.WANG Jingfei. Wind Power Accommodation Capacity Evaluation Model Based on Complex Network[J]. China Electric Power,2017(1):136-139,145.
[4]陈伟华,王刚,叶仁杰,et al.基于复杂网络理论的系统脆弱度评估新方法[J].浙江电力,2018,37(3):7-11.CHEN Weihua, WANG Gang, YE Renjie. A New Method for System Vulnerability Assessment Based on Complex Network Theory[J]. Zhejiang Electric Power, 2018, 37(3):7-11.
[5] KINNEY R, CRUCITTI P, ALBERT R, et al. Modeling cascading failures in the North American power grid[J].The European Physical Journal B,2005,46(1):101-107.
[6]白加林,刘天琪,曹国云,等.电力系统脆弱性评估方法综述[J].电网技术,2008,32(2):26-30.BAI Jialin, LIU Tianqi, CAO Guoyun, et al. Review of vulnerability assessment methods for power systems[J].Power System Technology, 2008, 32(2):26-30.
[7]马静,王希,王增平.基于线路运行介数的过负荷脆弱性评估[J].电网技术,2012,36(6):47-50.MA Jing, WANG Xi, WANG Zengping. Overload vulnerability assessment based on line operation line betweenness[J]. Power System Technology, 2012, 36(6):47-50.
[8] BOMPARD E, PONS E, WU D. Analysis of the structural vulnerability of the interconnected power grid of continental Europe with the Integrated Power System and Unified Power System based on extended topological approach[J]. International Transactions on Electrical Energy Systems,2013,23(5):620-637.
[9]徐林,王秀丽,王锡凡.电气介数及其在电力系统关键线路识别中的应用[J].中国电机工程学报,2010,30(1):33-39.XU lin, WANG Xiuli, WANG Xifan. Electrical median and its application in identifying key circuits of power system[J]. Journal of Electrical Engineering of China,2010, 30(1):33-39.
[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.
[11]王永翔,黄根,肖敏.特高压换流站GIS安装过程中的问题研究技术与应用[J].电气技术,2018,19(5):102-104.WANG Yongxiang, HUANG Gen, XIAO Min.Research on the problems in the installation of GIS inextra-high voltage converter station[J]. Electrical Technology, 2018, 19(5):102-104.
[12]张弘喆,赵康,李乐蒙,等.基于多层人工神经网络的电力系统恢复过电压预测[J].智慧电力,2018, 46(8):67-73.ZHANG Hongzhe, ZHAO Kang, LI Lemeng, et al.Overvoltage forecast during power system restoration based on multilayer artificial neural network[J]. Smart Power,2018, 46(8):67-73.
[13]王高红,陈潇一.基于遗传算法的智能电网非侵人式电器监控策略[J].智慧电力,2017,45(11):42-46.WANG Gaohong, CHEN Xiaoyi.Monitoring strategy with non-invasion for electric appliances in smart grid based on genetic algorithm[J]. Smart Power,2017,45(8):42-46.
[14] BOMPARD E, PONS E, WU D. Analysis of the structural vulnerability of the interconnected power grid of continental europe with the integrated power system and unified power system based on extended topological approach[J]. International Transactions on Electrical Energy Systems,2013,23(5):620-637.
[15]刘兆元,王萍,管志成.分布式电源大量接人后配电网可靠性综合评估体系[J].陕西电力,2016,44(10):15-19.LIU Zhaoyuan, WANG Ping, GUAN Zhicheng.Comprehensive evaluation system for distribution network reliability after large-scale access of distributed power supply[J]. Shaanxi Electric Power, 2016,44(10):15-19.
[16]孟华楠,胡晓波.基于相似模型泛函时间序列的短期电力负荷预测[J].陕西电力,2014,42(5):56-60.MENG Huanan, HU Xiaobo. Short time load prediction based on similar shape functional time-series[J]. Shaanxi Electric Power, 2014,42(5):56-60.
[17]蔡泽祥,王星华,任晓娜.复杂网络理论及其在电力系统中的应用研究综述[J].电网技术,2012,36(11):114-121.CAI Zexiang, WANG Xinghua, REN Xiaona. A review of complex network theory and its application in power systems[J]. Power Grid Technology, 2012, 36(11):114-121.
[18]张涛,孙晓伟,徐雪琴等.基于有功潮流介数的电网关键线路辨识[J].电网技术,2016,40(1):193-198.ZHANG Tao, SUN Xiaowei, XU Xueqin et al. Identification of critical lines in power grid based on active power flow betweenness[J]. Power Grid Technology, 2016, 40(1):193-198.