Ultrashort-term prediction method for wind electricity power of ARMA model with anemometer network real-time correction

Abstract

The invention discloses an ultrashort-term prediction method for wind electricity power of an ARMA model with anemometer network real-time correction. The ultrashort-term prediction method comprises the steps that model training processing is carried out on wind electricity power to be tested through the ARMA model with anemometer network real-time correction; ultrashort-term prediction is carried out on the wind electricity power to be tested based on a model training result of the wind electricity power to be tested. The ultrashort-term prediction method for the wind electricity power of the ARMA model with anemometer network real-time correction has the advantages that the detects that in an existing ARAM technology, ultrashort-term prediction of wind electricity power is low in accuracy and the like can be overcome, and high-precision ultrashort-term prediction of wind electricity power can be achieved.

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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