The invention provides a regional wind power prediction method and system based on space-time quantile regression. The method comprises the following steps: collecting the operation and numerical weather prediction data of a plurality of wind power plants in a preset time period, converting the collected data into a feature map, and building a training set, a verification set and a test set; establishing a space-time quantile regression model, and training and optimizing the model by utilizing the training set, the training set, the verification set and the test set; acquiring operation data and environment data of each wind power plant in real time, and predicting regional wind power generation in a certain time period in the future according to the optimized space-time quantile regression model. According to the invention, short-term non-parameterized probability prediction is carried out on regional wind power through the space-time quantile regression model; the selection problem of explanatory variables in regional wind power prediction with large input information is solved, the prediction accuracy and reliability are greatly improved, and a specific solution is provided forregional wind power generation probability prediction with big data.