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Journal of Zhejiang University SCIENCE A 2009 Vol.10 No.4 P.478~487

http://doi.org/10.1631/jzus.A0820130


Optimum allocation of FACTS devices in Fars Regional Electric Network using genetic algorithm based goal attainment


Author(s):  Mohsen GITIZADEH, Mohsen KALANTAR

Affiliation(s):  Center of Excellence for Power System Automation and Operation, Department of Electrical Engineering, Iran University of Science and Technology, Tehran 16844, Iran

Corresponding email(s):   gitizadeh@ee.iust.ac.ir

Key Words:  Flexible alternating current transmission system (FACTS) devices allocation, Multi-objective optimization, Genetic algorithm (GA), Goal attainment


Mohsen GITIZADEH, Mohsen KALANTAR. Optimum allocation of FACTS devices in Fars Regional Electric Network using genetic algorithm based goal attainment[J]. Journal of Zhejiang University Science A, 2009, 10(4): 478~487.

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Abstract: 
This paper presents a novel approach to find optimum locations and capacity of flexible alternating current transmission system (FACTS) devices in a power system using a multi-objective optimization function. Thyristor controlled series compensators (TCSCs) and static var compensators (SVCs) are the utilized FACTS devices. Our objectives are active power loss reduction, newly introduced FACTS devices cost reduction, voltage deviation reduction, and increase on the robustness of the security margin against voltage collapse. The operational and controlling constraints, as well as load constraints, were considered in the optimum allocation. A goal attainment method based on the genetic algorithm (GA) was used to approach the global optimum. The estimated annual load profile was utilized in a sequential quadratic programming (SQP) optimization sub-problem to the optimum siting and sizing of FACTS devices. Fars Regional Electric Network was selected as a practical system to validate the performance and effectiveness of the proposed method. The entire investment of the FACTS devices was paid off and an additional 2.4% savings was made. The cost reduction of peak point power generation implies that power plant expansion can be postponed.

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Reference

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