An ultra-short-term wind electricity power prediction method based on dynamic correlation characteristics

Abstract

The invention relates to an ultra-short-term wind electricity power prediction method based on dynamic correlation characteristics and belongs to the technical field of wind electricity power prediction. The method furthest utilizes the dynamic correlation characteristics of a wind electricity power time sequence, and makes accurate predictions by fully utilizing the recent change characteristics of wind electricity power on the basis of mastering the change rules of wind electricity power at different moments. The method can perform rolling prediction of wind electricity power in 0-4 hours, with the time interval being 15 minutes. The prediction method can guarantee the safety and stability of the operation of power grids, improve the wind electricity absorption capability and operation management efficiency of power grid companies, promote energy conservation and emission reduction, and bring huge economic and social benefit and has a favorable application prospect.

Description

technical field [0001] The invention belongs to the technical field of wind power forecasting, in particular to an ultra-short-term wind power forecasting method based on dynamic correlation features. Background technique [0002] With the rapid development of the world economy, the demand for energy has doubled, and the problems of energy and the environment have become increasingly prominent. Conventional energy directly emits greenhouse gases and aerosols into the atmosphere, causing global warming and increasingly serious environmental pollution, posing a serious threat to natural ecosystems, social economy and human health, which has attracted great attention from the international community and the public . In order to better overcome the constraints of the contradiction between energy supply and demand, promote the sustainable development of the global economy, cope with climate change, improve the living environment, and vigorously develop renewable energy including...

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Problems solved by technology

[0004] At present, domestic wind power forecasting is still in the stage of exploration and research, and its forecasting time is short, which cannot meet the needs of power system operation and scheduling.

Due to the difference in input data and prediction scale, the prediction error of wind power power is also different, especially in the wind power prediction under complex terrain, there is still a lack of successful prediction cases

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