Real-time wind power predicting method based on ensemble empirical mode decomposition and relevant vector machine

A technology that integrates empirical models and wind power prediction, applied in the field of wind power, can solve problems such as restricting the development of wind power

Inactive Publication Date: 2015-11-11
NORTHEAST DIANLI UNIVERSITY
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Problems solved by technology

Due to the volatility and randomness of wind energy itself, when the penetration power of wind power exceeds a certain value, it will bring severe challenges to the dispatching operation and power quality of the power system, which seriously limits the development of wind power.

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  • Real-time wind power predicting method based on ensemble empirical mode decomposition and relevant vector machine
  • Real-time wind power predicting method based on ensemble empirical mode decomposition and relevant vector machine
  • Real-time wind power predicting method based on ensemble empirical mode decomposition and relevant vector machine

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Embodiment Construction

[0045] The wind power real-time prediction method based on ensemble empirical mode decomposition and correlation vector machine of the present invention will be further described below in conjunction with the accompanying drawings and specific embodiments.

[0046] The wind power real-time prediction method based on ensemble empirical mode decomposition and correlation vector machine of the present invention comprises the following steps:

[0047] (1) Data acquisition and processing

[0048] The present invention takes the measured data of Xiangyang Wind Farm in Jilin Province in July 2012 as an example for analysis. The installed capacity of the wind farm is 400.5MW, the number of wind turbines is 267, the rated capacity of a single wind turbine is 1500kW, and the data sampling interval is 15 minutes;

[0049] (2) Establish a multi-step rolling forecast mode

[0050] When forecasting wind power, it is generally assumed that the current moment is recorded as i, and the sampl...

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Abstract

The invention discloses a real-time wind power predicting method based on ensemble empirical mode decomposition and a relevant vector machine. The real-time wind power predicting method is characterized by comprising the steps of obtaining and processing data, building a multi-step rolling prediction mode, building wind power prediction modules and prediction evaluating indexes of the ensemble empirical mode decomposition and the relevant vector machine, and the like. The real-time wind power predicting method has the advantages of being scientific, reasonable and capable of reducing influences brought by nonlinearity and nonstability wind power of wind power, meeting prediction precision requirements, facilitating electric power system dispatching, ensuring power energy quality, reducing the running cost, and the like.

Description

technical field [0001] The invention relates to the technical field of wind power, and relates to a real-time prediction method of wind power based on ensemble empirical mode decomposition and correlation vector machine. Background technique [0002] Changes in the global energy crisis have rapidly increased the demand for new energy. Wind energy is currently the most potential renewable energy for large-scale development and utilization. Wind power generation is an effective way to use wind energy on a large scale, and it is also a sustainable development strategy for energy and electricity in my country. the most realistic choice. However, in recent years, with the rapid growth of wind power installed capacity, the proportion of wind power in the grid has increased year by year. Due to the volatility and randomness of wind energy itself, when the penetration power of wind power exceeds a certain value, it will bring severe challenges to the dispatching operation and power ...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06Q10/04G06Q50/06
Inventor 杨茂张强
Owner NORTHEAST DIANLI UNIVERSITY
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