Eureka AIR delivers breakthrough ideas for toughest innovation challenges, trusted by R&D personnel around the world.

Day-ahead wind speed multistep prediction method fused with numerical weather prediction

A numerical weather forecast and wind speed technology, applied in electrical digital data processing, special data processing applications, instruments, etc., can solve the problems of low wind power prediction accuracy and large prediction error, meet the requirements of wind power grid connection, improve accuracy, The effect of mean relative error reduction

Inactive Publication Date: 2015-05-13
STATE GRID CORP OF CHINA +1
View PDF6 Cites 18 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0005] The purpose of the present invention is to propose a multi-step wind speed forecasting method that integrates numerical weather forecasting to solve the problems of large prediction error and low wind power prediction accuracy for the existing method of direct numerical weather forecasting fusion

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
  • Day-ahead wind speed multistep prediction method fused with numerical weather prediction
  • Day-ahead wind speed multistep prediction method fused with numerical weather prediction
  • Day-ahead wind speed multistep prediction method fused with numerical weather prediction

Examples

Experimental program
Comparison scheme
Effect test

specific Embodiment approach 1

[0025] Specific implementation mode one: combine figure 1 Describe this embodiment, a kind of day-ahead wind speed multi-step forecasting method that integrates numerical weather forecast described in this embodiment, comprises the following steps:

[0026] Step 1. Analyzing the information validity of the original wind speed sequence, determining the predictable duration of the statistical forecasting model, and obtaining the wind speed forecast results within the predictable duration;

[0027] Step 2. Analyze the information validity of the numerical weather prediction model, determine the predictable duration of the numerical weather prediction model, and obtain the wind speed forecast results within the predictable duration;

[0028] Step 3. According to the wind speed forecast results obtained in Step 1 and Step 2, fusion modeling is carried out according to the difference and complementarity between the numerical weather prediction model and the measured data, and the fu...

specific Embodiment approach 2

[0032] Specific implementation mode two: combination figure 2 , image 3 Describe this embodiment, the difference between this embodiment and specific embodiment one is: the process of analyzing the information validity of the original wind speed sequence described in step one, and determining the predictable duration of the statistical forecast model is:

[0033] Step one one, before using the statistical forecasting model, consider the multi-scale characteristics of the wind speed sequence, and use the wavelet decomposition algorithm to decompose the original wind speed sequence;

[0034] Step 12: Carry out autocorrelation analysis on each frequency subsequence obtained by wavelet decomposition of the original wind speed sequence, and determine the predictable duration of each frequency subsequence.

specific Embodiment approach 3

[0035] Specific implementation mode three: combination figure 2 , image 3 , Figure 4 Describe this embodiment, the difference between this embodiment and specific embodiment 1 or 2 is: the specific process of obtaining the wind speed forecast result within the predictable time length described in step 1 is:

[0036] Step 13: On the basis of steps 12, use a statistical forecasting model (such as an SVR model) on each frequency subsequence, and the model of each subsequence only predicts the wind speed within the forecastable time range of the subsequence. The wind speed forecast results within the predictable duration of each frequency subsequence are obtained, and the forecast results of the statistical forecast models of each subsequence are synthesized to obtain the wind speed forecast results of the statistical forecast model.

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 provides a day-ahead wind speed multistep prediction method fused with numerical weather prediction, and belongs to the technical field of wind speed prediction. The problems that an existing method is directly fused with numerical weather prediction, the prediction error is large, and the prediction precision of wind electricity power is low are solved. According to the technical scheme, the method comprises the steps of analyzing the information effectiveness of an original wind velocity sequence, determining the predictability time duration of a statistic forecasting model, obtaining the wind speed prediction result within a predicable time duration, conducting information effectiveness analysis on a numerical weather prediction model, determining the predicable time duration of the numerical weather prediction model, obtaining the wind speed prediction result within the predicable time duration, establishing a day-ahead wind speed fusion prediction model according to the wind speed prediction result and predicting the actual wind speed. The day-ahead wind speed multistep prediction method fused with numerical weather prediction is suitable for predicting the wind speed within day-ahead 24 hours in the future.

Description

technical field [0001] The invention relates to a novel multi-step forecast method of day-ahead wind speed, in particular to a multi-step forecast method of day-ahead wind speed integrated with numerical weather forecast (NWP), belonging to the technical field of wind speed forecast. Background technique [0002] Wind power generation is currently a hot topic in the research of the new energy power industry. However, because the wind is highly intermittent and uncontrollable, the wind power also fluctuates with the wind and is uncontrollable. This uncontrollability has changed the original operation mode of the power grid (injecting a strong random and uncertain power source on the power generation side), causing a serious impact on the power grid after large-scale wind power is connected to the grid, affecting the safe and stable operation of the power grid. Accurate prediction of wind power in wind farms is an important basis for solving this problem. It is helpful for gr...

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): G06F19/00
Inventor 郝文波赵雷雷徐冰亮孙承志赵志刚雷呈瑞任国瑞万杰郭钰锋
Owner STATE GRID CORP OF CHINA
Who we serve
  • R&D Engineer
  • R&D Manager
  • IP Professional
Why Eureka
  • Industry Leading Data Capabilities
  • Powerful AI technology
  • Patent DNA Extraction
Social media
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