Photovoltaic power generation short-term power rolling prediction method based on support vector machine algorithm

A support vector machine and power generation technology, applied in forecasting, information technology support systems, calculations, etc., can solve problems such as unfavorable power grid security dispatching and energy management, and increase the risk of power grid operation

Inactive Publication Date: 2017-03-15
TIANJIN UNIV
View PDF0 Cites 7 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

However, since the photovoltaic power generation system is significantly affected by environmental factors, it has characteristics such as uncertainty, volatility, and intermittency, which is not conducive to the safe dispatch and energy management of the power grid, and increases the operational risk of the power grid.

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
  • Photovoltaic power generation short-term power rolling prediction method based on support vector machine algorithm
  • Photovoltaic power generation short-term power rolling prediction method based on support vector machine algorithm
  • Photovoltaic power generation short-term power rolling prediction method based on support vector machine algorithm

Examples

Experimental program
Comparison scheme
Effect test

Embodiment Construction

[0019] The present invention will be described below in conjunction with the drawings and embodiments.

[0020] (1) Selection of similar days

[0021] The power output of photovoltaic systems is affected by many factors, including fixed environmental factors such as geographic location and irradiation angle, as well as variable environmental factors such as light intensity, temperature, humidity, cloud cover, and conversion efficiency, which are related to the characteristics of its own device. the elements of. Through analyzing the influence of different environmental factors on photovoltaic power generation, finally, the light intensity and temperature data that have the most obvious impact on photovoltaic power generation power are selected as the basis for judging environmental factors for similar days.

[0022] The selected daily weather feature vector is shown in the formula:

[0023] x i =[x i (1),x i (2),x i (3),x i (4)]=[t hi ,t li ,l hi ,l li ]

[0024] \*MERGEFORMAT(1)

[...

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 present invention relates to a photovoltaic power generation short-term power rolling prediction method based on a support vector machine algorithm. The generated power of a similar day and the current weather forecast of a predicated day are taken as the input amount of a prediction model, the photovoltaic power generation of the next day is predicated, after the next day is coming, the real output power of each predication point of the next day and the prediction power are continuously rolled forwards for comparison with the collection of the real power data, and when the predication points do not satisfy a given predication precision requirement, the real power of the current day and the real measurement weather data are taken as input data to establish a new PSO-SVM predication model so as to perform correction prediction of the power of the later-period predication points. The predication precision can be improved.

Description

Technical field [0001] The invention belongs to the technical field of photovoltaic power generation power prediction, and relates to a short-term power rolling prediction method of photovoltaic power generation. Background technique [0002] Photovoltaic power generation has the advantages of less pollution and flexible scale, and has been widely used. However, because the photovoltaic power generation system is obviously affected by environmental factors, it has the characteristics of uncertainty, volatility, and intermittentness, which is not conducive to the safe dispatch and energy management of the power grid, and increases the operation risk of the power grid. Therefore, predicting the short-term power of photovoltaic power generation can more comprehensively reflect the uncertainty of photovoltaic power generation, which is of great significance for grid planning and stable operation. [0003] The current forecasting methods for photovoltaic power generation power are most...

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
CPCG06Q10/04G06Q50/06Y04S10/50Y02A30/00
Inventor 王继东宋智林冉冉
Owner TIANJIN UNIV
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