Identification of optimal location of SVC through artificial intelligence techniques

In this paper, a stochastic search technique, namely Particle Swarm Optimization (PSO) is used to determine the optimal locations of two Static Var Compensators (SVCs) in an IEEE 14-bus system. Static Var compensators (SVC) are the most widely used shunt FACTS devices within power networks because o...

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Hauptverfasser: Sheeba, R., Jayaraju, M., Muhammed, Mansoor O., Shanavas, T. N., Sundareswaran, K.
Format: Tagungsbericht
Sprache:eng
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Zusammenfassung:In this paper, a stochastic search technique, namely Particle Swarm Optimization (PSO) is used to determine the optimal locations of two Static Var Compensators (SVCs) in an IEEE 14-bus system. Static Var compensators (SVC) are the most widely used shunt FACTS devices within power networks because of their smaller costs and significant system enhancements. Appeared about two decades ago, the SVC is mainly installed for voltage support and furthermore, when installed in a proper location, it can reduce the power loss. Here the problem is framed as an optimization task and the optimal locations of SVC are identified using the novel technique. The efficacy of the new algorithm is tested with extensive computer simulations and further compared with Genetic Algorithm (GA) based approach. The performance analysis is done through extensive simulations and shows that the proposed dispensation is on a par with existing techniques.
DOI:10.1109/ISET-India.2011.6145373