A power system stability evaluation method based on artificial intelligence method

With the proposal of carbon neutrality, more and more new energy sources are used. Assessing the stability of power systems integrated with these new energy sources has become an urgent issue. To address this challenge, an artificial intelligence-based method for steady-state analysis of power systems was proposed. This method employed both the Newton-Raphson method and PQ decomposition to calculate the power flow within the power system. Subsequently, artificial intelligence techniques were utilized to evaluate the reliability of the results by analyzing error characteristics. This approach differed from traditional artificial intelligence methods by incorporating generative adversarial network-based data set expansion technology and a multi-scale fusion neural network model. The final result is verified by the actual data of East China Power Grid, which shows the feasibility of the artificial intelligence algorithm.