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

Power system dynamic estimation method based on unscented Kalman particle filtering

An unscented Kalman and power system technology, applied in computing, electrical digital data processing, computer-aided design, etc., can solve problems such as lack of particles

Active Publication Date: 2019-08-23
NORTHEASTERN UNIV
View PDF3 Cites 10 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0005] The technical problem to be solved by the present invention is to provide a dynamic estimation method of power system based on unscented Kalman particle filter for the above-mentioned deficiencies in the prior art. Improve the proposed density distribution problem, can effectively improve the estimation accuracy, and effectively solve the problem of particle shortage

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
  • Power system dynamic estimation method based on unscented Kalman particle filtering
  • Power system dynamic estimation method based on unscented Kalman particle filtering
  • Power system dynamic estimation method based on unscented Kalman particle filtering

Examples

Experimental program
Comparison scheme
Effect test

Embodiment Construction

[0092] The specific implementation manners of the present invention will be further described in detail below in conjunction with the accompanying drawings and embodiments. The following examples are used to illustrate the present invention, but are not intended to limit the scope of the present invention.

[0093] Such as figure 1 As shown, the method of this embodiment is as follows.

[0094] The present invention provides a dynamic estimation method of power system based on unscented Kalman particle filter, comprising the following steps:

[0095] Step 1: Initialize the state variables of the current power system to obtain the particle swarm Φ at time k=0, where k represents time; the number of particles is N, Fori=1:N, from the prior probability density function p(X 0 ) to extract the initialization state As the initial state of the power system, calculate the initial state mean variance

[0096]

[0097]

[0098] where X0 =[v 0 θ 0 ],X 0 is the initial ...

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 power system dynamic estimation method based on unscented Kalman particle filtering, and relates to the technical field of power system monitoring, analysis and control. Themethod comprises the following steps: step 1, initializing a current state variable of the power system, and calculating an initial state mean value and variance; 2, setting k as 1; 3, carrying out importance sampling to obtain a particle swarm and a weight at the k moment; 4, carrying out particle swarm splitting and weight adjustment on the particle swarm; 5, judging whether Neff<Nth is established or not, if yes, turning to the step 6, and if not, turning to the step 8; 6, copying and eliminating the particle swarm to obtain a new particle swarm and weight; 7, carrying out weight normalization again; 8, calculating a state estimation value of the power system; and step 9, judging whether k >= Omega is established or not, if not, setting k = k + 1, and turning to the step 3, and ending the dynamic estimation of the power system if so. According to the method, the suggested density distribution problem is improved, the estimation precision can be effectively improved, and the problemof particle shortage is effectively solved.

Description

technical field [0001] The invention relates to the technical field of power system monitoring, analysis and control, in particular to a power system dynamic estimation method based on unscented Kalman particle filter. Background technique [0002] With the continuous development of society, people have higher and higher requirements for the stability of power system. In order to improve the stability of the power system, we must improve the scheduling, control, safety assessment and other aspects of the power system. Power system dynamic estimation is the basis of power system dispatching, control, safety assessment, etc. Dynamic state estimation can carry out safety assessment of power system through state prediction, and realize online functions such as economic dispatching and preventive control. The importance is self-evident. In view of this, we must quickly and accurately conduct dynamic estimation of the power system. [0003] In the early 1970s, Debs and others pr...

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): G06F17/50G06Q10/06G06Q50/06
CPCG06Q10/063G06Q50/06G06F30/20Y02E60/00
Inventor 黄博南李明肖军刘鑫蕊孙秋野杨珺刘振伟马大中胡经纬王睿
Owner NORTHEASTERN 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