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124398

IMPROVED GENERATION QUALITY OF AN ISOLATED WIND DRIVEN INDUCTION GENERATOR USING ARTIFICIAL NEURAL NETWORK

Article

Last updated: 26 Dec 2024

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Subjects

-

Tags

Electrical Engineering, Computer Engineering and Electrical power and machines engineering.

Abstract

This paper presents the improvement of generation quality for a wind energy conversion scheme using artificial neural network (ANN). High generation quality means that, the induction generator generate voltages and frequency at nominal specified values, under all operating conditions, determined by various wind speeds and loads. The scheme consists of a three-phase induction generator driven by a horizontal axis wind turbine and interfaced to an isolated load. A static VAR compensator (SVC) is connected at the induction generator terminals to regulate its voltage. The mechanical power input is controlled by regulating the blade pitch-angle. Both blade pitch-angle and firing angle are adjusted using an ANN to improve the generation quality for a wind energy conversion scheme. The proposed ANN training is based on suitable values of SVC firing angles and blade pitch-angles of the wind turbine, for achieving a high generation quality at different operating conditions. The training data is obtained by using Newton-Raphson method to generate voltages and frequency at nominal specified values. The simulation results prove that, the wind energy conversion scheme, with the proposed ANN, gives good power generation quality over wide range of wind speeds and loads.

DOI

10.21608/jesaun.2010.124398

Authors

First Name

Yehia S.

Last Name

Mohamed

MiddleName

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Affiliation

Electrical Eng. Dept., Faculty of Engineering, El-Minia University, El- Minia, Egypt

Email

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City

-

Orcid

-

First Name

B. M.

Last Name

Hasaneen

MiddleName

-

Affiliation

Electrical Eng. Dept., Faculty of Engineering, Al-Azhar University, Qena, Egypt

Email

-

City

-

Orcid

-

First Name

Mohamed Abd-El- Hakeem

Last Name

Mohamed

MiddleName

-

Affiliation

Electrical Eng. Dept., Faculty of Engineering, Al-Azhar University, Qena, Egypt

Email

-

City

-

Orcid

-

Volume

38

Article Issue

No 3

Related Issue

16848

Issue Date

2010-05-01

Receive Date

2010-03-10

Publish Date

2010-05-01

Page Start

783

Page End

796

Print ISSN

1687-0530

Online ISSN

2356-8550

Article File

JESAUN_Volume 38_Issue No 3_Pages 783-796.pdf

PDF . 257.3kB

Link

https://jesaun.journals.ekb.eg/article_124398.html

Detail API

https://jesaun.journals.ekb.eg/service?article_code=124398

Order

12

Type

Research Paper

Type Code

1,438

Publication Type

Journal

Publication Title

JES. Journal of Engineering Sciences

Publication Link

https://jesaun.journals.ekb.eg/

MainTitle

IMPROVED GENERATION QUALITY OF AN ISOLATED WIND DRIVEN INDUCTION GENERATOR USING ARTIFICIAL NEURAL NETWORK

Details

Type

Article

Created At

23 Jan 2023