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

Frequency estimation method for three-phase power system

A three-phase power, system frequency technology, applied in the field of frequency estimation, can solve problems, grid faults, serious convergence problems, etc.

Inactive Publication Date: 2019-01-15
XIAN UNIV OF TECH
View PDF5 Cites 7 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

An incorrect estimation of the frequency of a three-phase power system may lead to a catastrophic failure of the grid. Therefore, the design of fast and accurate frequency estimation techniques in the presence of varying noise and unbalanced three-phase voltages is essential.
[0003] The traditional adaptive filtering method only considers the Gaussian output noise of the system when estimating the frequency of the three-phase power system, and often ignores the influence of input noise and non-Gaussian noise on the accuracy of system frequency estimation. The adaptive filtering algorithm has a large deviation when it is applied to the system with input noise; the adaptive filtering algorithm based on the deviation compensation recursive least squares solves the problem that the system is mixed with input noise, but when the output noise contains non- When Gaussian noise is used, its convergence will have serious problems and even diverge
In fact, as an adaptive filter, the input voltage signal is often disturbed by noise, and the system output measurement noise also often has non-Gaussian characteristics

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
  • Frequency estimation method for three-phase power system
  • Frequency estimation method for three-phase power system
  • Frequency estimation method for three-phase power system

Examples

Experimental program
Comparison scheme
Effect test

Embodiment 1

[0140] The NLMS, NLMF, and BCNMF algorithms are compared with the BCNLMS algorithm when the input and output noises are Gaussian noise. As shown in Figure 2(a), BCNLMS is superior to other algorithms in terms of convergence speed and accuracy, as shown in Figure 2( b) shows that when the mean square error (MSE) of the BCNLMS and NLMS algorithms through 500 Monte Carlo experiments varies between 0.05-0.4, the BCNLMS algorithm has a clear advantage.

Embodiment 2

[0142] When the input noise is Gaussian noise and the output noise is uniform noise, compare the performance of NLMS algorithm, NLMF algorithm, BCNLMS algorithm and BCNLMF algorithm. As shown in Figure 3(a), BCNLMF has better convergence accuracy and speed Advantages, Figure 3(b) shows that when the mean square error (MSE) of the BCNLMF and NLMS algorithms through 500 Monte Carlo experiments changes between 0.35-0.6 in the noise variance, BCNLMF still has a clear advantage; Figure 3(c) shows When the output noise is replaced by binary noise, the comparison chart of the performance of each algorithm shows that the BCNLMF algorithm still has good performance in the background of binary noise. Figure 3(d) shows that the BCNLMF and NLMF algorithms pass 500 Monte Carlo The Luo experiment compared the MSE of each algorithm when the noise variance was 0.1-0.8, and verified the robustness of the BCNLMF algorithm.

Embodiment 3

[0144] The performance of each algorithm when the voltage amplitude of each phase of the power system changes. Figure 4(a) is the three-phase unbalanced voltage waveform when the voltage amplitude changes; Figure 4(b) is the input of the three-phase unbalanced voltage The performance comparison chart of the frequency estimation of each algorithm under the condition that the output noise and the output noise obey the Gaussian distribution shows that the BCNMS algorithm is superior to the NLMS algorithm, NLMF algorithm, and BCNLME algorithm in terms of frequency estimation accuracy and speed; Figure 4(c) shows that the output noise is non-Gaussian Robustness of the BCNLMF algorithm in the presence of noise.

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 frequency estimation method for a three-phase power system, comprising the following steps: Step 1, acquiring three-phase voltage signals with noise of va(k), vb(k) and vc(k)in a three-phase power system, wherein k represents k time; step 2, transforming the three-phase voltage signals of va(k), vb(k) and vc(k) into a three-phase complex voltage vn(k) by the Clarke transform, and adding a three-phase voltage complex signal obtained by measuring the noise; Step 3, establishing a linear model of {vn(k), vn(k+1)} according to the three-phase voltage complex signal; Step4, using the offset compensation adaptive filtering algorithm to estimate the weight term w(k) in the linear model, obtaining a weight iteration formula after adding a deviation compensation term, and then substituting the weight iteration formula into a frequency estimation formula to obtain a frequency estimate of the three-phase power system.

Description

technical field [0001] The invention belongs to the technical field of frequency estimation methods, and relates to a three-phase power system frequency estimation method. Background technique [0002] For a long time, the real-time estimation and monitoring of power system frequency has played an extremely important role in the safe operation of three-phase power systems. Among them, engineering problems such as parameter measurement, fault diagnosis, harmonic compensation and power quality control are inseparable from fast and accurate , Reliable frequency real-time estimation. The wrong estimation of the frequency of the three-phase power system may lead to catastrophic failure of the power grid. Therefore, the design of fast and accurate frequency estimation technology in the presence of different noises and unbalanced three-phase voltage is essential. [0003] The traditional adaptive filtering method only considers the Gaussian output noise of the system when estimati...

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): G01R23/02
CPCG01R23/02
Inventor 马文涛邱进哲张志禹郑栋桥
Owner XIAN UNIV OF TECH
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