Short-term wind power prediction method

A technology for wind power and short-term forecasting, applied in electrical components, circuit devices, AC network circuits, etc., can solve problems such as inaccurate wind power forecasting

Inactive Publication Date: 2013-03-06
NORTH CHINA ELECTRIC POWER UNIV (BAODING)
View PDF3 Cites 2 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0006] Aiming at the inaccurate prediction of wind power mentioned in the above background technology, the present invention proposes a short-term prediction method of wind power

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

Examples

Experimental program
Comparison scheme
Effect test

Embodiment Construction

[0052] The preferred embodiments will be described in detail below in conjunction with the accompanying drawings. It should be emphasized that the following description is only exemplary and not intended to limit the scope of the invention and its application.

[0053] The data processed by ridgelet transform form a new sample set, and selecting the optimal sample from the sample set is the premise of predicting wind power. For this reason, the present invention introduces a quantum evolutionary algorithm to extract optimal samples, which uses qubit codes to represent chromosomes, makes full use of the correlation of qubits, and completes population evolution with quantum revolving door updates. A quantum revolving door operation will simultaneously act on the composition On all the ground states of the superposition state, each ground state interferes with each other through the quantum revolving door to change their phases, so that the probability amplitude of each ground st...

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 short-term wind power prediction method in the technical field of wind power prediction. Wind speed information and corresponding wind power data are acquired in 30 hours before a prediction day, and noise elimination treatment is carried out to the collected initial data by ridgelet transform, so that a sample set is formed by the processed data; an optimal sample is selected by quantum-inspired evolutionary algorithm; and the selected optimal sample is used as a training sample of a direct-push support vector machine for carrying out training, and the wind power prediction is carried out by utilizing the trained direct-pushing support vector machine. The short-time wind power prediction method has better adaptability and higher detection precision in the aspect of predicting short-term wind power.

Description

technical field [0001] The invention belongs to the technical field of wind power forecasting, in particular to a short-term wind power forecasting method. Background technique [0002] Wind energy is a clean and renewable energy source. Due to its good economic and social benefits, wind power generation has been highly valued by countries all over the world. Due to the uncontrollability of wind, the prediction of wind power is particularly important, especially the short-term prediction of wind power can effectively reduce the impact of wind power grid-connected on the entire power grid, and help the power system dispatching department to arrange dispatching plans more reasonably. [0003] At present, the prediction methods of wind power can be divided into two categories: one is the numerical weather prediction method, and the other is the prediction method based on historical data. [0004] Based on the numerical weather prediction is to use the numerical weather predict...

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 Patents(China)
IPC IPC(8): H02J3/00G06K9/62
CPCY02A30/00
Inventor 李元诚杨瑞仙
Owner NORTH CHINA ELECTRIC POWER UNIV (BAODING)
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
Try Eureka
PatSnap group products

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

© 2024 PatSnap. All rights reserved.Legal|Privacy policy|Modern Slavery Act Transparency Statement|Sitemap