Title :
Identification of optimal location of SVC through artificial intelligence techniques
Author :
Sheeba, R. ; Jayaraju, M. ; Muhammed, Mansoor O. ; Shanavas, T.N. ; Sundareswaran, K.
Author_Institution :
Dept. of Electr. & Electron. Eng., T.K.M. Coll. of Eng., Kollam, India
Abstract :
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.
Keywords :
artificial intelligence; flexible AC transmission systems; genetic algorithms; particle swarm optimisation; static VAr compensators; GA-based approach; IEEE 14-bus system; PSO; SVC optimal location; artificial intelligence technique; genetic algorithm; particle swarm optimization; power loss reduction; power networks; shunt FACTS devices; static Var compensators; stochastic search technique; IEEE standards; Optimization; Power system stability; Reactive power; Static VAr compensators; Voltage control; FACTS; Particle Swarm Optimization (PSO); Static VAR compensators (SVC);
Conference_Titel :
Innovative Smart Grid Technologies - India (ISGT India), 2011 IEEE PES
Conference_Location :
Kollam, Kerala
Print_ISBN :
978-1-4673-0316-3
DOI :
10.1109/ISET-India.2011.6145373