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

Active distribution network measurement optimization and configuration method containing node injection power uncertainty

A node injection power and uncertainty technology, applied in the field of active distribution network measurement optimization configuration, can solve the uncertainty of electric vehicle charging load without detailed elaboration and modeling, time-consuming, poor global convergence, etc. problems, to achieve the effect of easier search, lower operating costs, and faster convergence

Active Publication Date: 2016-06-29
SOUTHEAST UNIV
View PDF1 Cites 8 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0006] 2) The impact of large-scale electric vehicle charging load on the distribution network is ignored, and the uncertainty of electric vehicle charging load is not elaborated and modeled in detail;
[0007] 3) The genetic algorithm used in solving the established mathematical model has disadvantages such as time-consuming and poor global convergence

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
  • Active distribution network measurement optimization and configuration method containing node injection power uncertainty
  • Active distribution network measurement optimization and configuration method containing node injection power uncertainty
  • Active distribution network measurement optimization and configuration method containing node injection power uncertainty

Examples

Experimental program
Comparison scheme
Effect test

Embodiment

[0021] Embodiment: Based on the existing theoretical research, the present invention characterizes PEV charging randomness and DG output intermittency with dynamic probability density function, and establishes active distribution network measurement (data collection point) to optimize the configuration model, and use the CMA-ES algorithm to optimize the model, so that the optimal configuration scheme of the data collection point can be obtained under the condition that the network is fully observable, which can effectively reduce the system operating cost, and can be an active The next step of distribution network security assessment provides theoretical support.

[0022] The specific steps of an optimal configuration method for active distribution network measurement (data collection point) including node injection power uncertainty in this embodiment are as follows figure 1 shown, including:

[0023] Step 1: Use the dynamic probability density function to model and analyze ...

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 an active distribution network measurement optimization and configuration method containing node injection power uncertainty. The uncertainties of a large-scale electric vehicle charging load and photovoltaic power generation system output are modeled and analyzed by a dynamic probability density function; the network observability of the active distribution network after containing the node injection power uncertainty is analyzed from a state evaluation angle; an active distribution network measurement optimization and configuration model containing the node injection power uncertainty is established; and the active distribution network measurement optimization and configuration model is optimized and solved by adopting an adaptive covariance matrix evolutionary strategy to obtain a data acquisition point optimal configuration scheme under the premise of ensuring the complete observability of the network. By adoption of the method, the shortcoming that the electric vehicle charging randomness and the photovoltaic power generation system output intermittence are neglected in the current distribution network situation awareness program is overcome; theoretical support for further safety evaluation of the active distribution network is supplied; and in addition, the safe operation and control economical efficiency of the active distribution network can be further improved.

Description

technical field [0001] The invention relates to an active distribution network, in particular to a measurement optimization configuration method for an active distribution network. Background technique [0002] The access of high-penetration distributed generation (distributed generation, DG), large-scale electric vehicle (plug-inelectric vehicle, PEV) and energy storage system (energy storage system, ESS) and other controllable loads makes the traditional one-way radial distribution network Gradually transform into an active distribution network (active distribution network, ADN) that includes a multi-energy power supply system and, if necessary, operates in a weak ring topology. At the same time, the distribution network situation awareness system is expected to be able to further quickly and accurately perceive the real-time operating status of the system, laying the foundation for the safe and stable operation of the power grid. [0003] However, on the one hand, due to...

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): H02J3/00G06Q10/04G06Q50/06
CPCG06Q10/04G06Q50/06H02J3/00H02J2203/20
Inventor 吴在军徐俊俊戴桂木窦晓波周力
Owner SOUTHEAST 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