Dynamic security assessment method based on principal component analysis and convolutional neural network

The invention relates to a dynamic security assessment method based on principal component analysis and a convolutional neural network, which specifically comprises the following steps of: 1, obtaining a system operation data sample, constructing a dynamic security index, and forming a corresponding initial sample set; 2, generating an efficient sample set; 3, updating the efficient sample set, and completing the updating of an evaluation model; and 4, based on the real-time operation data of a power system, completing evaluation of the real-time dynamic security state of the power system by using the continuously updated dynamic security evaluation model to obtain a final online dynamic security evaluation result. According to the online dynamic security model of the power system, rapid,efficient and accurate prediction and evaluation can be provided for the power system, system maintenance and safety measure prevention work of power personnel are facilitated, the safety and stability of operation of the pow