Research on power grid security situation awareness based on linear discriminant analysis and RBF neural network

With the Internet of Things transformation of power information network construction, the development and research of smart grids are becoming more and more intelligent at present. The open network architecture and diverse power demands make the power system increasingly complex and bring huge uncertainties to the construction and operation of the power system. To ensure the safe and stable operation of the power grid, this paper proposes a grid security situation awareness evaluation method based on linear discrimination and RBF neural network. This method first uses linear discriminant analysis (LDA) to optimize the dimensionality reduction preprocessing of sample data, and then uses the training data of the RBF neural network model to realize the perception of power system network security situation.