Optimal Locating and Sizing of SSSC using Genetic Algorithm in Deregulated Power Market | Zendy

Seyed Mohammad Hossein Nabavi | Zendy; Kamran Khafafi | Zendy; Aidin Sakhavati | Zendy; Saeid Nahi | Zendy

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Optimal Locating and Sizing of SSSC using Genetic Algorithm in Deregulated Power Market

Author(s) -

Seyed Mohammad Hossein Nabavi,

Kamran Khafafi,

Aidin Sakhavati,

Saeid Nahi

Publication year - 2011

Publication title -

international journal of computer applications

Language(s) - English

Resource type - Journals

ISSN - 0975-8887

DOI - 10.5120/2569-3532

Subject(s) - sizing , computer science , genetic algorithm , mathematical optimization , power (physics) , power market , operations research , algorithm , electric power system , machine learning , mathematics , chemistry , physics , quantum mechanics , organic chemistry

The aim of this paper is presenting a genetic algorithm based method for congestion management and to maximize social welfare using one unit Static Synchronous Series Compensator (SSSC) in a double auction pool market based power systems. The aims are achieved by optimal locating and sizing one SSSC unit. In this paper, the GenCos cost functions are considered to be the quadratic form. Simulation outcomes on the modified IEEE 14 bus test system are used to show the impact of SSSC unit on the congestion management and social welfare maximization. Inclusion of the benefit functions of customer in the objective function and the utilization of a GA based algorithm for optimal locating/sizing of SSSC to guarantee fast convergence to the global optimal solution are the main contributions. Keywordssocial welfare maximization; congestion management; deregulated power market; genetic algorithms; SSSC; optimal power flow

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