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128695

Proposed Scheme for Characterization of Power Quality Disturbances.

Article

Last updated: 22 Jan 2023

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Subjects

-

Tags

Electrical Engineering

Abstract

A voluminous amount of disturbance waveforms are captured and recorded by power quality survey projects. These disturbances need to be automatically classified and characterized to provide informative and useful results about the power quality condition of the system. Intensive research is conducted to accomplish efficient automatic classification tools. There is still a notable scarcity in apt techniques for characterization or quantification of disturbances. In this paper, a scheme based on discrete wavelet transform and neural networks is proposed to characterize the recorded power quality disturbances. A routine is presented to compute the disturbance duration. A dedicated neural network is used to estimate the duration-magnitude product of the disturbance. The design and structure of the neural estimator is addressed. An alternative scheme for designing the estimator is also proposed and described. The performance of the two methods is tested with many disturbances of 6 different types. The results are compared to select the best estimators relevant to each disturbance type. 

DOI

10.21608/bfemu.2020.128695

Authors

First Name

Akram Ibrahim

Last Name

El-Mitwally

MiddleName

Mohamed

Affiliation

Elect. Eng. Dept., Mansoura University, Mansoura, 35516. Egypt

Email

-

City

Mansoura

Orcid

-

First Name

A.

Last Name

Abdelmageid

MiddleName

-

Affiliation

Elect. Eng. Dept., Mansoura University, Mansoura, 35516. Egypt

Email

-

City

Mansoura

Orcid

-

First Name

S.

Last Name

Fathy

MiddleName

-

Affiliation

Elect. Eng. Dept., Mansoura University, Mansoura, 35516. Egypt

Email

-

City

Mansoura

Orcid

-

Volume

32

Article Issue

3

Related Issue

19077

Issue Date

2007-09-01

Receive Date

2007-07-11

Publish Date

2020-12-09

Page Start

17

Page End

25

Print ISSN

1110-0923

Online ISSN

2735-4202

Article File

BFEMU_Volume 32_Issue 3_Pages 17-25.pdf

PDF . 1.2MB

Link

https://bfemu.journals.ekb.eg/article_128695.html

Detail API

https://bfemu.journals.ekb.eg/service?article_code=128695

Order

4

Type

Research Studies

Type Code

1,205

Publication Type

Journal

Publication Title

MEJ. Mansoura Engineering Journal

Publication Link

https://bfemu.journals.ekb.eg/

MainTitle

-

Details

Type

Article

Created At

22 Jan 2023