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88881

Optimization PI Controller Parameters for VSC-HVDC System based on Particle-Swarm-Optimization.

Article

Last updated: 22 Jan 2023

Subjects

-

Tags

Electrical Engineering

Abstract

Nowadays the HVDC systems are considered as basic devices in the new electrical networks because they could solve many problems such as connections of different frequencies regions. Networks stability is the aim of many researchers. They used conventional methods such as PI controllers for this purpose in these methods. The parameters of PI controllers were assumed depending on the operator's experiences. The authors of this paper optimized the system parameters using Particle Swarm Optimization (PSO). A comparative study between the conventional and optimized systems will be presented. The obtained results show the efficient performance of the designed system 

DOI

10.21608/bfemu.2020.88881

Keywords

Optimization, HVDC-VSC, DC-link, PI, PSO. MATLAB, Simulink

Authors

First Name

Eid

Last Name

Goda

MiddleName

Abd El Baky

Affiliation

Electrical Department, Faculty of Engineering - Mansoura University

Email

eid.gouda@yahoo.com

City

Mansoura

Orcid

-

First Name

Ebrahim

Last Name

Mansy

MiddleName

Ebrahim

Affiliation

Electrical Engineering Department, Mansoura University, Egypt

Email

-

City

Mansoura

Orcid

-

First Name

Ayman

Last Name

Ebrahim

MiddleName

Bdrawy

Affiliation

Electrical Engineering Department, Mansoura University, Egypt

Email

bdrawy@gmail.com

City

Mansoura

Orcid

-

Volume

42

Article Issue

2

Related Issue

13234

Issue Date

2017-06-01

Receive Date

2017-02-19

Publish Date

2020-05-13

Page Start

8

Page End

14

Print ISSN

1110-0923

Online ISSN

2735-4202

Link

https://bfemu.journals.ekb.eg/article_88881.html

Detail API

https://bfemu.journals.ekb.eg/service?article_code=88881

Order

6

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