The invention provides a day-ahead transaction
strategy method and
system based on market supply and demand and regional meteorological prediction, and the method comprises the steps: obtaining regional prediction meteorological data and
station prediction meteorological data, and obtaining market supply and demand prediction data and historical power
transaction data; carrying out data preprocessing; modeling the preprocessed data by adopting a multi-
task learning method in
deep learning to obtain a prediction model for
electric power transaction market pre-judgment; inputting regional prediction meteorological data,
station prediction meteorological data and market supply and demand prediction data of the D day, and predicting market pre-judgment information of power transaction of the Dday through the prediction model; and substituting the historical medium and long term average price, the
electric field installed capacity, the short term prediction of the
station and the market pre-judgment information into the optimization model, and solving the day-ahead 96-point power
declaration and the expected strategy income. The method and
system can adapt to scenes of multiple tasks,strong correlation among the tasks can be fully utilized, the prediction accuracy is improved, and the generalization ability of the model is greatly enhanced.