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

Short-term wind power combination prediction method

A combined forecasting and wind power technology, applied in electrical digital data processing, instrumentation, computing, etc., can solve problems such as reducing signal non-stationarity, and achieve the effect of low cost, easy promotion, and high forecasting accuracy.

Inactive Publication Date: 2013-12-04
WUHAN UNIV
View PDF2 Cites 10 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0004] The nonlinear and non-stationary characteristics of wind power are the main reasons that affect the prediction effect. Effective decomposition of wind power signals with a certain scale or fluctuation trend can reduce the non-stationarity of the signal

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
  • Short-term wind power combination prediction method
  • Short-term wind power combination prediction method
  • Short-term wind power combination prediction method

Examples

Experimental program
Comparison scheme
Effect test

Embodiment

[0041] First of all, the relevant theoretical basis involved in the present invention is introduced.

[0042] 1. Principle of Ensemble Empirical Mode Decomposition

[0043] Empirical mode decomposition is essentially an adaptive signal screening method, which can filter out the trend of different characteristics existing in the original sequence step by step, and obtain the intrinsic mode component (intrinsic mode function, IMF) with the same characteristics. The modal component needs to meet two conditions (1) and (2): (1) the difference between the number of zeros and the number of poles in the entire natural mode component sequence is at most one; (2) at any point, it is defined by a local minimum point The mean value of the envelope defined by the envelope and the local maximum point is 0.

[0044] For a wind power time series {x(t)}, the steps of empirical mode decomposition are as follows:

[0045] 1) Find all the maximum and minimum values ​​in the sequence {x(t)}. U...

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 relates to a short-term wind power combination prediction method which comprises steps of 1, extracting wind power sequential data from supervisory control and data acquisition (SCADA) related to a wind power plant; 2, performing sequence analysis on the extracted wind power sequential data through ensemble empirical mode decomposition; 3, reconstructing phase space of sequences obtained through the ensemble empirical mode decomposition; 4, according to the data obtained by reconstructing the phase space of the sequences, training the established wavelet neural network prediction model, and superposing predication results of the sequences to obtain a wind power prediction result; 5, performing error analysis on the wind power prediction result. By means of the short-term wind power combination prediction method, the modeling process is simple and practical, and wind power predication can be quickly and effectively performed. Therefore, the short-term wind power combination prediction method has great significance in safety, stability, management and running of a power system, and has wide popularization and application value.

Description

technical field [0001] The invention relates to a short-term wind power combination prediction method. Background technique [0002] 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 quality of the power system, which seriously limits the development of wind power. If the wind power can be effectively predicted, it will not only reduce the reserve capacity of the power system and reduce the operating cost of the system, but also reduce the adverse impact of wind power on the power grid, effectively increase the maximum installed capacity of wind power in the power system, and improve the competitiveness of wind power. . [0003] The currently commonly used short-term wind power forecasting...

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
IPC IPC(8): G06F19/00
Inventor 胡志坚王贺
Owner WUHAN UNIV
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