大数据视角下的电网基本故障分析判断

Basic Grid Failure Analysis and Judgment from Big Data Perspective

采用大数据分析方法中的多维随机矩阵,处理电力网络中故障前后的数据信息,以随机矩阵的谱半径作为评价依据进行故障判定与定位,通过分析随机矩阵谱半径的特征与变化实现故障分析进而实现判断和预警。在对大数据方法的基本数学理论及应用思路进行介绍的基础上,采用新英格兰10机39节点网络的仿真实例进行计算,验证了大数据方法应用于智能电网故障判断的有效性与可行性。

Large multidimensional data analysis methods were used to deal with random matrix data before and after the power network fault,the spectral radius of random matrices as a basis for evaluating the fault determination and positioning,to achieve fault analysis by analyzing the characteristics and changes in the spectral radius of random matrices thus achieving judgment and warning. This paper described the basic mathematical theory of large data method and a simulation example of New England 39-node network was used to verify the calculation,while comparing with other traditional fault identification method,which proves big data approach in smart grid fault diagnosis is effective and feasible.