Wind power cluster power ultra-short-term prediction error grade grading compensation method

Abstract

The embodiment of the invention provides a wind power cluster power ultra-short-term prediction error grade grading compensation method. The method comprises the steps that according to correlation groups of all wind power plants in a wind power cluster, an active power time sequence, at the current moment, of all the wind power plants included in each correlation group is input into a power prediction model corresponding to the correlation group, and a preliminary prediction result, at the next moment, of the active power of all the wind power plants included in the correlation group is output; and error level grading is performed according to the error of the active power prediction result of each wind power plant at the last moment and the current moment in the wind power cluster, errorcompensation is performed on the initial prediction result of the active power of the wind power plant at the next moment according to the error level grading result, and the prediction result of theactive power of the wind power plant at the next moment is acquired. According to the wind power cluster power ultra-short-term prediction error grade grading compensation method provided by the embodiment of the invention, error compensation is more accurate, and the power prediction precision can be improved.

Description

technical field [0001] The invention relates to the technical field of wind power generation, and more specifically, to a method for graded compensation of ultra-short-term prediction error levels of wind power cluster power. Background technique [0002] With the depletion of non-renewable resources such as coal and oil and the increasing environmental pollution, clean, safe and pollution-free renewable energy sources such as wind energy, solar energy, tidal energy and biomass energy have attracted more and more attention. Among them, wind power is the renewable energy with the most mature technology and the most development value, and the integration of large-scale wind power into the power grid as the main power source is the future development trend. [0003] The intermittent nature of wind energy in nature determines that wind power has strong fluctuations and uncertainties. With the continuous increase in the number and installed capacity of wind farms, once wind power...

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Problems solved by technology

[0006] The embodiment of the present invention provides a wind power cluster power ultra-short-term prediction error level classification compensation method to solve or at least partially solve the defect of insufficient prediction accuracy caused by inaccurate compensation in the prior art

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