GENETIC ALGORITHM BASED FUZZY MULTI-OBJECTIVE APPROACH TO FACTS DEVICES ALLOCATION IN FARS REGIONAL ELECTRIC NETWORK

Q: How can I download an article?

To download an article from SID, first log in to the site, search for the article title, and click on the 'Download Article' option.

Q: How can I download an ISI article?

To download an ISI article on SID, enter the keyword or article title in the search bar, view the relevant results, click on the desired article, and select the 'Download Article' option.

Q: How can I access the SID database?

To access the SID database, visit SID.ir, create an account, and log in to access scientific resources.

Q: Is downloading articles from SID free?

Some articles on SID are available for free, while others require payment. Details are specified on the article's page.

GITIZADEH M.; KALANTAR M.

مرکز اطلاعات علمی Scientific Information Database (SID) - Trusted Source for Research and Academic Resources

Journal Paper

Paper Information

Journal: Scientia Iranica Year:2008 | Volume:15 | Issue:6 Page(s): 534-546

Download Full-Text

View:

338

Download:

260

Cites:

Information Journal Paper

Title

GENETIC ALGORITHM BASED FUZZY MULTI-OBJECTIVE APPROACH TO FACTS DEVICES ALLOCATION IN FARS REGIONAL ELECTRIC NETWORK

Author(s)

GITIZADEH M. | KALANTAR M. | Issue Writer Certificate

Keywords

FACTS DEVICES ALLOCATION

MULTI-OBJECTIVE OPTIMIZATION

GENETIC ALGORITHM

FUZZY

Abstract

In this investigation, a novel approach is presented to find the optimum locations and capacity of Flexible AC Transmission Systems (FACTS) devices in a power system using a FUZZY multi-objective function. Maximising the FUZZY satisfaction allows the optimization algorithm to simultaneously consider the multiple objectives of the network to obtain active power loss reduction; i.e., new FACTS devices cost reduction, robustifying the security margin against voltage collapse, network loadability enhancement and a voltage deviation reduction of the power system. A GENETIC ALGORITHM (GA) optimization technique is then implemented to solve the FUZZY multi-objective problem. Operational and control constraints, as well as load constraints, are considered for optimum device allocation. Also, an estimated annual load profile has been utilized in a Sequential Quadratic Programming (SQP) optimization sub-problem to find the optimum location and capacity of FACTS devices, accurately. A Thyristor Controlled Series Compensator (TCSC) and a Static Var Compensator (SVC) are utilized as series and shunt FACTS devices in this study. The Fars regional electric network is selected as a practical system to validate the performance and effectiveness of the proposed method.

Multimedia

No record.

Cites

No record.

References

No record.

Cite

APA: Copy

GITIZADEH, M., & KALANTAR, M.. (2008). GENETIC ALGORITHM BASED FUZZY MULTI-OBJECTIVE APPROACH TO FACTS DEVICES ALLOCATION IN FARS REGIONAL ELECTRIC NETWORK. SCIENTIA IRANICA, 15(6), 534-546. SID. https://sid.ir/paper/289730/en

Vancouver: Copy

GITIZADEH M., KALANTAR M.. GENETIC ALGORITHM BASED FUZZY MULTI-OBJECTIVE APPROACH TO FACTS DEVICES ALLOCATION IN FARS REGIONAL ELECTRIC NETWORK. SCIENTIA IRANICA[Internet]. 2008;15(6):534-546. Available from: https://sid.ir/paper/289730/en

IEEE: Copy

M. GITIZADEH, and M. KALANTAR, “GENETIC ALGORITHM BASED FUZZY MULTI-OBJECTIVE APPROACH TO FACTS DEVICES ALLOCATION IN FARS REGIONAL ELECTRIC NETWORK,” SCIENTIA IRANICA, vol. 15, no. 6, pp. 534–546, 2008, [Online]. Available: https://sid.ir/paper/289730/en

Related Journal Papers

No record.

Related Seminar Papers

No record.

Related Plans

No record.

Recommended Workshops