Day-ahead transaction strategy method and system based on market supply and demand and regional meteorological prediction

Abstract

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.

Description

technical field [0001] The invention belongs to the field of electric power trading, and in particular relates to a day-ahead trading strategy method and system based on market supply and demand and regional weather forecast. Background technique [0002] Due to the volatility and randomness of new energy, especially wind power, how to design trading strategies so that new energy power generation companies can rationally complete mid-to-long-term plans and at the same time rationally arbitrage in spot transactions to maximize profits is an important issue for all new energy power generation companies problem. Through the prediction of the future clearing situation, formulate corresponding day-ahead trading strategies, and through reasonable quotations, new energy power generation companies can increase the revenue of power spot transactions in power spot transactions, while reducing risks. [0003] Shortcoming and deficiency of prior art are as follows: [0004] 1) Failure...

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Problems solved by technology

[0006] 3) Insufficient analysis of the composition and interrelationships of power trading revenues, failing to consider the relative relationship of each revenue as a whole;

[0007] 4) The existing model lacks timeliness information such as cross-sectional topology diagrams and ultra-short-term load conditions, which increases the uncertainty of transaction revenue estimation

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