Power grid static voltage stability margin probability prediction method considering new energy uncertainty

The invention relates to a power grid static voltage stability margin probability prediction method considering new energy uncertainty. The power grid static voltage stability margin probability prediction method specifically comprises the following steps: constructing a power prediction error model of new energy represented by wind power and photovoltaic; constructing a wind power and photovoltaic static scene generation model based on a prediction error model and Monte Carlo sampling; constructing a single-scene static voltage stability margin prediction method based on deep learning; and generating a power grid static voltage stability margin probability prediction result considering the new energy uncertainty by adopting a kernel density estimation method. The method has the following advantages: on one hand, the scene generation model based on the new energy prediction error considers the randomness of new energy power generation, and the obtained static voltage stability margin probability distribution