Data-driven high-proportion renewable energy power system operation scene identification method

A renewable energy and power system technology, applied in the direction of electrical digital data processing, special data processing applications, information technology support systems, etc., can solve the problems of identifying high-proportion renewable energy power system operating scenarios and their changing laws The effect of improving identification ability and improving operation efficiency

Active Publication Date: 2021-01-26
TSINGHUA UNIV +1
View PDF3 Cites 0 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0006] However, there are no reports on the use of data-driven methods to identify hig

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
  • Data-driven high-proportion renewable energy power system operation scene identification method
  • Data-driven high-proportion renewable energy power system operation scene identification method
  • Data-driven high-proportion renewable energy power system operation scene identification method

Examples

Experimental program
Comparison scheme
Effect test

Example Embodiment

[0054]The present invention proposes a data-driven high-proportion renewable energy power system operation scenario identification method. The following further describes the present invention in detail with reference to the drawings and specific embodiments.

[0055]The present invention provides a data-driven high-proportion renewable energy power system operation scenario identification method, and the overall process is as followsfigure 1 As shown, including the following steps:

[0056]1) Refined operation simulation of the power system to be identified, and obtain the daily operation mode vector of the system;

[0057]Obtain power system load data, unit information, network topology information, renewable resources and their temporal and spatial correlation information from the power system operation planning department (the load data and renewable resource information are hourly data throughout the year), and use TH-DSED Software for fine operation simulation of power system (TH-DSED ...

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 data-driven high-proportion renewable energy power system operation scene identification method, and belongs to the technical field of power system operation. The method comprises the following steps: firstly, carrying out refined operation simulation on a to-be-identified power system to obtain a daily operation mode vector corresponding to the system; preprocessing all daily operation mode vectors by using a principal component analysis method to obtain a preprocessed power system operation mode matrix; determining a typical operation scene of the power system through a Kmeans + + algorithm and the compactness index of the operation mode of the power system; and realizing visualization of the operation characteristics by utilizing a t-SNE algorithm to obtain an extreme operation scene. According to the method, a typical scene in planning and operation can be effectively determined by using a data driving method, an extreme operation mode in protection and stability analysis can be rapidly identified, important reference can be provided for planning and operation personnel of a power system, and the analysis capability of the high-proportion renewable energy power system is improved.

Description

technical field [0001] The invention belongs to the technical field of power system operation, and in particular relates to a data-driven high-proportion renewable energy power system operation scene identification method. Background technique [0002] Grid-connected power generation with a high proportion of renewable energy (in the present invention refers to the proportion of renewable energy exceeding 30%) has become an important technical means for the power system to achieve low-carbon and clean transformation. As of the end of 2019, China's grid-connected wind power and grid-connected photovoltaic installed capacity reached 209GW and 204GW respectively, ranking first in the world. The strong uncertainty of the high proportion of renewable energy and the complex dynamics of the high proportion of power electronics have brought multiple challenges to the power system, such as diversified operation modes, bidirectional power grid flow, and complex stability mechanisms. ...

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): G06F30/20G06K9/62G06F113/04G06F113/06
CPCG06F30/20G06F2113/04G06F2113/06G06F18/23213G06F18/2135Y04S10/50
Inventor 侯庆春杜尔顺田旭张宁张子扬刘飞张君张桂红李红霞白左霞
Owner TSINGHUA 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