王耀升,张英敏,王畅,漆万碧.基于RBF神经网络的电网脆弱性评估及其趋势估计[J].电测与仪表,2019,56(9):49-55. wang yaosheng,zhang yingmin,wang chang,qi wanbi.Power Grid Vulnerability Assessment Based on RBF Neural Network and its Vulnerability Trend Estimation[J].Electrical Measurement & Instrumentation,2019,56(9):49-55.
基于RBF神经网络的电网脆弱性评估及其趋势估计
Power Grid Vulnerability Assessment Based on RBF Neural Network and its Vulnerability Trend Estimation
This paper establishes the hierarchical network topology of network vulnerability evaluation system. The system was proposed based on radial basis function (RBF) neural network method of grid vulnerability assessment. The comprehensive vulnerability of the power grid is divided into the state vulnerability and structural vulnerability, and the corresponding sub-indexes constitute the vulnerability network evaluation system. At the same time, with Gauss functions as the kernel function of RBF neural network function to solve nonlinear problem between the indicators. By using the RBF neural network function in MATLAB, the calculation and analysis of IEEE14 bus system is carried out to verify the comprehensiveness and effectiveness of the method. Finally, For multiple nodes of the measurement cycle vulnerability measure establishing auto regressive (AR) model, the AR model is to determine the stability of difference equation and analyse the development trend of node vulnerability measure.
