基于传染病模型的电网扰动传播动力学分析
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摘要
研究电网扰动传播动力学行为对大电网安全稳定运行具有重要作用。该文在研究电网扰动传播动力学时尝试借助生物学中成熟的传染病模型进行研究。首先,在类比传染病模型的基础上,提出电网扰动传播强度的概念;进一步利用复杂网络理论对复杂电力系统网络进行拓扑分析,利用随机矩阵理论对电网时空数据进行关联关系分析;最后,基于数据驱动建立电网扰动传播动力学模型,对电网扰动传播行为进行预测。仿真结果表明,所提模型是传统电网扰动传播分析的有效补充,为电网扰动传播动力学行为分析提供新途径。
Study on the dynamic behavior of disturbance propagation is important for the safety and stability of power grid. The research of the dynamic disturbance analysis attempts to use mature epidemic model of biology. First, based on the analogy epidemic model and the transmission of the grid disturbance, the concept of disturbance transmission intensity was put forward. Furthermore, the complex network theory was used to analyze the complex network topology of the power system, and the random matrix theory was used to analyze the relationship between the spatial and temporal data of the power grid. At last, the dynamic model of power grid disturbance propagation based on data driven was established.The simulation shows that the proposed model can effectively supplement the traditional power system disturbance propagation analysis, and also can analyze the dynamic behavior of power grid.
Study on the dynamic behavior of disturbance propagation is important for the safety and stability of power grid. The research of the dynamic disturbance analysis attempts to use mature epidemic model of biology. First, based on the analogy epidemic model and the transmission of the grid disturbance, the concept of disturbance transmission intensity was put forward. Furthermore, the complex network theory was used to analyze the complex network topology of the power system, and the random matrix theory was used to analyze the relationship between the spatial and temporal data of the power grid. At last, the dynamic model of power grid disturbance propagation based on data driven was established.The simulation shows that the proposed model can effectively supplement the traditional power system disturbance propagation analysis, and also can analyze the dynamic behavior of power grid.
引文
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[17]赵腾,张焰,张东霞.智能配电网大数据应用技术与前景分析[J].电网技术,2014,38(12):3305-3312.Zhao Teng,Zhang Yan,Zhang Dongxia.Application technology of big data in smart distribution grid and its prospect analysis[J].Power System Technology,2014,38(12):3305-3312(in Chinese).
[18]He Xing,Ai Qian,Qiu R C,et al.A big data architecture design for smart grids based on random matrix theory[J].IEEE Transactions on Smart Grid,2017,8(2):674-686.
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[22]Xu Xinyi,He Xing,Ai Qian,et al.A correlation analysis method for power systems based on random matrix theory[J].IEEE Transactions on Smart Grid,2017,8(4):1811-1820.
[23]徐心怡,贺兴,艾芊,等.基于随机矩阵理论的配电网运行状态相关性分析方法[J].电网技术,2016,40(3):781-790.Xu Xinyi,He Xing,Ai Qian,et al.A correlation analysis method for operation status of distribution network based on random matrix theory[J].Power System Technology,2016,40(3):781-790(in Chinese).
[2]Tamronglak S,Horowitz S H,Phadke A G,et al.Anatomy of power system blackouts:preventive relaying strategies[J].IEEE Transactions on Power Delivery,1996,11(2):708-715.
[3]鞠平,刘咏飞,薛禹胜,等.电力系统随机动力学研究展望[J].电力系统自动化,2017,41(1):1-8.Ju Ping,Liu Yongfei,Xue Yusheng,et al.Research prospects for stochastic dynamics of power system[J].Automation of Electric Power Systems,2017,41(1):1-8(in Chinese).
[4]李春艳,孙元章,陈向宜,等.西欧“11.4”大停电事故的初步分析及防止我国大面积停电事故的措施[J].电网技术,2006,30(24):16-21.Li Chunyan,Sun Yuanzhang,Chen Xiangyi,et al.Preliminary analysis of large scale blackout in western Europe power grid on November 4 and measures to prevent large scale blackout in China[J].Power System Technology,2006,30(24):16-21(in Chinese).
[5]张恺.交直流混联电网大扰动稳定特性分析与控制策略研究[D].北京:华北电力大学,2014.Zhang Kai.Research on the stability and control of AC/DC power system subjected to a severe disturbance[D].Beijing:North China Electric Power University,2014(in Chinese).
[6]马宁宁.基于分布式流体网络的电力系统机电扰动传播研究[D].成都:西南交通大学,2013.Ma Ningning.Study on electromechanical disturbance propagation in power systems based on distributed fluid network[D].Chengdu:Southwest Jiaotong University,2013(in Chinese).
[7]燕跃豪.基于WAMS的电力系统扰动传播机理研究[D].北京:华北电力大学(北京),2014.Yan Yuehao.Study on the power system disturbance propagation mechanism based on WAMS[D].Beijing:North China Electric Power University,2014(in Chinese).
[8]马颖,张园园,宋文广.食品行业突发事件风险感知的传染病模型研究[J].科研管理,2013,34(9):123-130.Ma Ying,Zhang Yuanyuan,Song Wenguang.Research on epidemic model of emergency events risk perception in food industry[J].Science Research Management,2013,34(9):123-130(in Chinese).
[9]杨青,刘星星,陈瑞青,等.基于免疫系统的非常规突发事件风险识别模型[J].管理科学学报,2015,18(4):49-61.Yang Qing,Liu Xingxing,Chen Ruiqing,et al.Risk identification model of unconventional crisis based on immune system[J].Journal of Management Sciences in China,2015,18(4):49-61(in Chinese).
[10]Wang Jianrong,Liu Maoxing,Li Youwen.Analysis of epidemic models with demographics in metapopulation networks[J].Physica A:Statistical Mechanics and its Applications,2013,392(7):1621-1630.
[11]孙玺菁,司守奎.复杂网络算法与应用[M].北京:国防工业出版社,2015.Sun Xijing,Si Shoukui.Complex network algorithms and applications[M].Beijing:National Defend Industry Press,2015(in Chinese).
[12]韩忠明,吴杨,谭旭升,等.面向结构洞的复杂网络关键节点排序[J].物理学报,2015,64(5):058902.Han Zhongming,Wu Yang,Tan Xusheng,et al.Ranking key nodes in complex networks by considering structural holes[J].Acta Physica Sinica,2015,64(5):058902(in Chinese).
[13]吴茜,张东霞,刘道伟,等.基于随机矩阵理论的电网静态稳定态势评估方法[J].中国电机工程学报,2016,36(20):5414-5420.Wu Qian,Zhang Dongxia,Liu Daowei,et al.A method for power system steady stability situation assessment based on random matrix theory[J].Proceedings of the CSEE,2016,36(20):5414-5420(in Chinese).
[14]Chu C C,Iu H H C.Complex networks theory for modern smart grid applications:A survey[J].IEEE Journal on Emerging and Selected Topics in Circuits and Systems,2017,7(2):177-191.
[15]Jia Yanbing,Liu Ruiqiong,Han Xiaoqing,et al.Risk assessment of cascading failures in power grid based on complex network theory[C]//Proceedings of the 14th International Conference on Control,Automation,Robotics and Vision(ICARCV).Phuket,Thailand:IEEE,2016.
[16]张东霞,苗新,刘丽平,等.智能电网大数据技术发展研究[J].中国电机工程学报,2015,35(1):2-12.Zhang Dongxia,Miao Xin,Liu Liping,et al.Research on development strategy for smart grid big data[J].Proceedings of the CSEE,2015,35(1):2-12(in Chinese).
[17]赵腾,张焰,张东霞.智能配电网大数据应用技术与前景分析[J].电网技术,2014,38(12):3305-3312.Zhao Teng,Zhang Yan,Zhang Dongxia.Application technology of big data in smart distribution grid and its prospect analysis[J].Power System Technology,2014,38(12):3305-3312(in Chinese).
[18]He Xing,Ai Qian,Qiu R C,et al.A big data architecture design for smart grids based on random matrix theory[J].IEEE Transactions on Smart Grid,2017,8(2):674-686.
[19]Qiu R C,Hu Z,Li H,et al.Cognitive communications and networking:Theory and practice[M].New York:John Wiley and Sons,2012:42-43.
[20]Qiu R,Antonik P.Big data and smart grid:A random matrix[M].New York:John Wiley and Sons,2015.
[21]Qiu R C,Hu Zhen,Chen Zhe,et al.Cognitive radio network for the smart grid:experimental system architecture,control algorithms,security,and microgrid testbed[J].IEEE Transactions on Smart Grid,2011,2(4):724-740.
[22]Xu Xinyi,He Xing,Ai Qian,et al.A correlation analysis method for power systems based on random matrix theory[J].IEEE Transactions on Smart Grid,2017,8(4):1811-1820.
[23]徐心怡,贺兴,艾芊,等.基于随机矩阵理论的配电网运行状态相关性分析方法[J].电网技术,2016,40(3):781-790.Xu Xinyi,He Xing,Ai Qian,et al.A correlation analysis method for operation status of distribution network based on random matrix theory[J].Power System Technology,2016,40(3):781-790(in Chinese).