A wind power forecasting method based on variable mode decomposition and long-short memory network

Abstract

The invention discloses a wind power prediction method based on a variable mode decomposition and a long-short memory network. Firstly, the wind power signal is decomposed into three modal componentssuch as a long-term sub-component, a fluctuation number and a random component according to the characteristics of the wind power. Then, the long-short memory network is used to learn the modal components of wind power, and the prediction model is established. Finally, the prediction values are synthesized. The method can obtain the random characteristics of wind power and improve the accuracy andstep size of wind power forecasting.

Description

technical field [0001] The invention belongs to the technical field of electric power system control, and in particular relates to a wind power prediction method combining variable mode decomposition and long-short memory network. Background technique [0002] The uncertainty brought about by the inherent volatility and randomness of wind power will cause the imbalance of power generation and supply, and bring a series of difficulties to the power system. Improving the accuracy of wind power forecasting is an effective means to solve these problems, so it has been a research hotspot for a long time. [0003] Wind power is divided into prediction methods based on physical models and statistical models. The method based on physical model relies on meteorological data, and its implementation is more complicated. The prediction method based on statistical model establishes the linear or nonlinear mapping between the actual value and the predicted value time series by summarizi...

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Problems solved by technology

However, it is difficult to select the wavelet basis function in the wavelet method, and it is difficult to obtain the delay time and embedding dimension in the phase space reconstruction technology. The empirical mode decomposition method depends on experience and lacks a theoretical basis for the decomposition of wind power signals.

Now some scholars have begun to study the stratification of wind power signal by using variable mode decomposition, but the number of decomposition layers is difficult to determine

And pursue the accuracy of decomposition and reconstruction, ignoring the characteristics of wind power itself

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