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Issue title: Special section: Recent trends, Challenges and Applications in Cognitive Computing for Intelligent Systems
Guest editors: Vijayakumar Varadarajan, Piet Kommers, Vincenzo Piuri and V. Subramaniyaswamy
Article type: Research Article
Authors: Kirn Kumar, N. | Indra Gandhi, V.; *
Affiliations: School of Electrical Engineering, Vellore Institute of Technology, Vellore, India
Correspondence: [*] Corresponding author. V. Indra Gandhi, Associate Professor, School of Electrical Engineering, Vellore Institute of Technology, Vellore, India. E-mail: arunindra08@gmail.com.
Abstract: As the world is moving towards green energy generation to reduce the pollution by renewable sources such as wind, solar, geothermal and more. These sources are intermittent in nature, to coordinate and control with traditional power generating units a control technique is necessary. This paper mainly focuses on the design of fuzzy based classical controller using a PSO algorithm for optimal controller gains to control the frequency variations in island hybrid power system. The considered mathematical model comprises of a diesel generating model, wind turbine generator and a battery storage system. Fuzzy is an intelligent controller which is designed with trial and error rules or on the basis of past experience provided by experts or by optimization methods for optimized gains using computational algorithms. To give best solution for these kinds of problems with FLCs traditional controllers are integrated with fuzzy logic. The PSO algorithm is applied to tune the classical controller gains to decrease the frequency deviation of the island power system, during the different load and wind disturbances. The Fuzzy PID classical controller shows the best performance compared with the only fuzzy and Fuzzy-PI controller configurations by illustrating the under shoot, overshoot and settling time and the proposed method is robust for various loading conditions and different wind changes.
Keywords: Battery energy storage, fuzzy logic controller, load frequency control, particle swarm optimization, renewable energy sources
DOI: 10.3233/JIFS-189147
Journal: Journal of Intelligent & Fuzzy Systems, vol. 39, no. 6, pp. 8273-8283, 2020
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