An ultra-short-term wind power prediction method based on arma model with real-time correction of wind measurement network

Abstract

The invention discloses an ultra-short-term wind power prediction method based on an ARMA model corrected by an anemometer network in real time. As a result, an ultra-short-term forecast is made for the wind power to be measured. The ARMA model wind power ultra-short-term prediction method for real-time correction of the wind measurement network described in the present invention can overcome the defects of low wind power ultra-short-term prediction accuracy in the existing ARMA technology, so as to realize the advantages of high-precision wind power ultra-short-term prediction.

Description

technical field [0001] The invention relates to the technical field of ultra-short-term forecasting of wind power in the process of new energy power generation, in particular to an ultra-short-term forecasting method of wind power using an ARMA model for real-time correction of a wind measurement network. Background technique [0002] Most of the large-scale new energy bases generated after my country's wind power enters the stage of large-scale development are located in the "three north regions" (Northwest, Northeast, and North China). Large-scale new energy bases are generally far away from the load center, and their power needs to be transmitted to load center for consumption. Due to the intermittence, randomness and volatility of wind and light resources, the output of wind power and photovoltaic power generation in large-scale new energy bases will fluctuate in a large range, which will further lead to fluctuations in the charging power of the transmission network, whic...

AI Technical Summary

Problems solved by technology

The ARMA method has many advantages, so it is widely used in ultra-short-term forecasting of wind power, but the biggest disadvantage of ARMA is the hysteresis of its prediction—that is, when the wind power output changes, the change speed of the ARMA predicted result is generally slower than the actual wind power output. The rate of change, therefore, seriously affects the predictive accuracy of ARMA

[0005] In the process of realizing the present invention, the inventors found that there are at least some defects in the existing ARMA technology such as low ultra-short-term prediction accuracy of wind power in the prior art

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