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Wind speed prediction method the basis of self excitation threshold autoregression model

An autoregressive model and wind speed prediction technology, applied in the field of power transmission and distribution

Inactive Publication Date: 2017-04-26
NORTH CHINA ELECTRIC POWER UNIV (BAODING)
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Problems solved by technology

[0005] The technical problem to be solved by the present invention is to provide a wind speed prediction method based on the self-excited threshold autoregressive model (i.e. the SETAR model), aiming at the disadvantages of the existing prediction methods and the significant nonlinear characteristics of the wind speed sequence, so as to achieve more accurate Wind speed forecast to optimize power grid dispatch and planning

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  • Wind speed prediction method the basis of self excitation threshold autoregression model

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Embodiment 1

[0065] The data set used in the embodiment comes from a wind farm in Spain, where there are four distinct seasons, and the three months of each quarter have similar characteristics, so the embodiment selects one month of each quarter as a representative. Therefore, the actual data used in the embodiment is the sampling data in November 2015, February, May and August 2016. The actual wind speed distribution of the four-month data is as follows: figure 1 shown. Table 1 provides an overview of the selected data.

[0066] figure 1 (a)-(d) represent the actual wind speeds of Spanish wind farms in February, May, August and November 2015, respectively.

[0067] Table 1 Detailed statistics of wind speed data of Spanish wind farms in November 2015, February, May and August 2016

[0068]

[0069] Ramsey [] introduced a test of the functional form of least squares linear regression analysis. This test is called the RESET test. Consider the linear AR(p) (the present invention con...

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Abstract

The invention provides a wind speed prediction method the basis of a self excitation threshold autoregression model, belongs to the power transmission and distribution technology field and aims to improve an original wind speed prediction method and improve wind speed prediction precision. According to the method, an original non-linear wind speed sequence is divided into multiple sequences through an SETAR model on the basis of a threshold r and a lag order d, an AR model is established for each sequence segment, the model is an AR model actually or a segmented AR model controlled by the threshold r; an optimal prediction value is determined according to a prediction result. The method is advantaged in that non-linear characteristics of the wind speed sequence are fully mined, on the basis, the proper regression model is established. As proved by a test result, compared with a traditional prediction method on the basis of an ARMA model and a BP model, the method has higher prediction precision.

Description

technical field [0001] The invention relates to a method capable of accurately predicting the magnitude of wind speed and then predicting the power of a wind farm, belonging to the technical field of power transmission and distribution. Background technique [0002] The development of human civilization is inseparable from energy, and energy is the foundation of our human development. Due to the disadvantages of limited reserves of fossil energy and the generation of environmentally harmful gases due to incomplete combustion, the era of fossil fuels as the main body will eventually pass away and be gradually replaced by new energy. Today, how to develop new energy without polluting the environment is a common concern of mankind. Of course, this is also an important issue of concern for China's current development. The shortage of energy and the aggravation of the greenhouse effect make the search for new renewable energy Energy, changing the energy structure has become a ma...

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Application Information

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IPC IPC(8): G06Q10/04G06Q50/06
CPCG06Q10/04G06Q50/06
Inventor 赵征王晓亮汪向硕张亚刚勾海芝杨蕃
Owner NORTH CHINA ELECTRIC POWER UNIV (BAODING)
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