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

Multi-time-scale prediction method of photovoltaic generation power

A photovoltaic power generation and multi-time scale technology, applied in the field of power systems, can solve problems that are difficult to solve large-scale data problems and are not suitable for processing massive, rich and refined photovoltaic power generation data, etc., to achieve fast parallel processing capabilities and solve a large number of problems. The effect of enriching photovoltaic power data problems and enhancing adaptability

Inactive Publication Date: 2018-06-26
STATE GRID JIANGSU ELECTRIC POWER CO WUXI POWER SUPPLY CO +1
View PDF3 Cites 27 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

Traditional forecasting methods have good forecasting accuracy and operating efficiency for small sample data, but are difficult to solve large-scale data problems, and are not suitable for processing massive, rich and refined photovoltaic power generation data

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
  • Multi-time-scale prediction method of photovoltaic generation power
  • Multi-time-scale prediction method of photovoltaic generation power
  • Multi-time-scale prediction method of photovoltaic generation power

Examples

Experimental program
Comparison scheme
Effect test

Embodiment Construction

[0055]Specific embodiments of the present invention will be described in detail below in conjunction with the accompanying drawings. It should be understood that the specific embodiments described here are only used to illustrate and explain the present invention, and are not intended to limit the present invention.

[0056] As an aspect of the present invention, a multi-time scale prediction method for photovoltaic power generation is provided, wherein, such as figure 1 As shown, the photovoltaic power generation multi-time scale prediction method includes:

[0057] S110. Obtain basic data required for forecasting photovoltaic power generation, wherein the basic data include season type, weather type, temperature, wind speed and historical photovoltaic power generation;

[0058] S120, classifying the historical photovoltaic power generation power in the same season according to the weather type;

[0059] S130. Establish a feature set for photovoltaic power generation data 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 the technical field of power systems, and particularly discloses a multi-time-scale prediction method of photovoltaic generation power. The multi-time-scale prediction methodof the photovoltaic generation power includes: acquiring basic data required for photovoltaic generation power prediction, wherein the basic data include season types, weather types, temperature, windspeed and historical photovoltaic generation power; classifying historical photovoltaic generation power of the same season according to the weather types; establishing a feature set for photovoltaicgeneration power data under the same weather type; establishing a photovoltaic generation power prediction model of a deep ridgelet neural network (DRNN) according to the feature set; and acquiring amulti-time-scale prediction result of the photovoltaic-method generation power through the established photovoltaic generation power prediction model of the deep ridgelet neural network. The multi-time-scale prediction method of the photovoltaic generation power provided by the invention has the advantages of high running efficiency and high prediction precision.

Description

technical field [0001] The invention relates to the technical field of power systems, in particular to a multi-time scale prediction method for photovoltaic power generation. Background technique [0002] With the increasing penetration rate of new energy such as wind energy and photovoltaics in the power generation capacity of the power system year by year, while alleviating energy shortages and environmental degradation, the intermittent and unstable nature of wind energy and photovoltaic power generation also contributes to the safety and reliability of the power grid. , Economic operation poses great challenges. Accurate photovoltaic power forecasting predicts photovoltaic output within a certain period of time in the future, which can provide scientific decision-making basis for grid automatic power generation control and grid dispatching, thereby effectively reducing the impact of large-scale photovoltaic access on the power system and ensuring grid security and econom...

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): G06Q10/04G06Q50/06
CPCG06Q10/04G06Q50/06Y02E40/70Y04S10/50
Inventor 俞娜燕李向超费科孙国强梁智
Owner STATE GRID JIANGSU ELECTRIC POWER CO WUXI POWER SUPPLY CO
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