Looking for breakthrough ideas for innovation challenges? Try Patsnap Eureka!

Wind power plant ultrashort term wind speed prediction method based on combination kernel function

A combined kernel function and wind speed forecasting technology, applied in forecasting, data processing applications, instruments, etc., can solve problems such as affecting the accuracy of wind speed forecasting

Inactive Publication Date: 2013-04-24
UNIV OF ELECTRONICS SCI & TECH OF CHINA
View PDF4 Cites 18 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

However, a single kernel function has its application limitations, which will directly affect the accuracy of wind speed prediction

Method used

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
View more

Image

Smart Image Click on the blue labels to locate them in the text.
Viewing Examples
Smart Image
  • Wind power plant ultrashort term wind speed prediction method based on combination kernel function
  • Wind power plant ultrashort term wind speed prediction method based on combination kernel function
  • Wind power plant ultrashort term wind speed prediction method based on combination kernel function

Examples

Experimental program
Comparison scheme
Effect test

Embodiment

[0096] Taking the historical wind speed data of a wind farm in June 2012 as the original data, the number of training samples is 882, and the number of prediction samples is 378.

[0097] This embodiment sets the autocorrelation threshold r T is 70%, according to the embedding dimension The corresponding embedding dimension D=2 at this time is obtained. Normalize the training samples. According to the embedding dimension D, the support vector machine model training sample input matrix P and output matrix Q are obtained as:

[0098] P = x ~ 1 , x ~ 2 x ~ 2 ...

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to View More

PUM

No PUM Login to View More

Abstract

The invention discloses a wind power plant ultrashort term wind speed prediction method based a combination kernel function. The method comprises the following steps: adopting a support vector machine based on the combination kernel function, combining a wavelet kernel function and a polynomial kernel function, combining a global characteristic of the polynomial kernel function with high precision and good learning capacity of the wavelet kernel function, effectively improving predictive capacity of a support vector machine model, and reducing predicting errors. Meanwhile, in building of the support vector machine model, choosing similar data, building models in a classified mode, enabling a training sample and a test sample to have a similar relation, and therefore strengthening nonlinear fitting capacity of a support vector regression model. According to combination of the combination kernel function and the similar data, the wind power plant ultrashort term wind speed prediction method based the combination kernel function improves precision of wind speed prediction.

Description

technical field [0001] The invention belongs to the technical field of ultra-short-term wind speed prediction in wind power generation systems, and more specifically relates to a method for ultra-short-term wind speed prediction of wind farms based on combined kernel functions. Background technique [0002] At present, the research on various topics of wind power generation at home and abroad is getting more and more in-depth. As an intermittent energy source, wind power has great randomness and uncontrollability. The fluctuation range of its output power is usually large and the speed is fast. As a result, it is very difficult to control the peak load, reactive power and voltage of the power grid, and bring new problems to the safety, stability and normal dispatch of the power grid. [0003] Common methods for wind speed prediction based on historical data include continuation method, Kalman filter method, random time series method, neural network method, fuzzy logic method...

Claims

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to View More

Application Information

Patent Timeline
no application Login to View More
Patent Type & Authority Applications(China)
IPC IPC(8): G06Q10/04G06Q50/06
Inventor 凡时财邹见效徐红兵李文茹
Owner UNIV OF ELECTRONICS SCI & TECH OF CHINA
Who we serve
  • R&D Engineer
  • R&D Manager
  • IP Professional
Why Patsnap Eureka
  • Industry Leading Data Capabilities
  • Powerful AI technology
  • Patent DNA Extraction
Social media
Patsnap Eureka Blog
Learn More
PatSnap group products

Browse by: Latest US Patents, China's latest patents, Technical Efficacy Thesaurus, Application Domain, Technology Topic, Popular Technical Reports.

© 2024 PatSnap. All rights reserved.Legal|Privacy policy|Modern Slavery Act Transparency Statement|Sitemap|About US| Contact US: help@patsnap.com