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Article type: Research Article
Authors: Laghari, J.A.; | Mokhlis, Hazlie; | Abu Bakar, Ab Halim | Mohamad, Hasmaini
Affiliations: Department of Electrical Engineering, Faculty of Engineering, University of Malaya, Kuala Lumpur, Malaysia | University of Malaya Power Energy Dedicated Advanced Centre (UMPEDAC), Level 4, Wisma R&D UM, Jalan Pantai Baharu, University of Malaya, Kuala Lumpur, Malaysia | Faculty of Electrical Engineering, University of Technology MARA (UiTM), Shah Alam, Selangor, Malaysia | Department of Electrical Engineering, Quaid-e-Awam University of Engineering Science & Technology, Nawabshah, Sindh, Pakistan
Note: [] Corresponding author. J.A. Laghari, E-mails: javedahmedleghari@gmail.com; hazli@um.edu.my (H. Mokhlis); a.halim@um.edu.my (A.H. Abu Bakar); hasmaini@hotmail.com (H. Mohamad).
Abstract: Mini hydro power plants (MHPP) are gaining attraction as a cost effective source for rural electrification in developing countries due to its environmental friendly operation. These MHPP plants suffer from the speed control problem due to continuous load variation. PID controllers fail to provide optimum speed control due to its limitation of parameter tuning. Alternatively, Fuzzy logic control is commonly used for implementing intelligent control for the nonlinear system. This paper presents a new fuzzy logic based governor for frequency/speed regulation of MHPP for implementation in distribution network. For verification, the response of load frequency control using fuzzy based governor and PID based governor is compared. The simulation results show that fuzzy based governor ensures robust control by improving the frequency response as well as dynamic response in comparison to PID based governor. Furthermore, fuzzy based governor enables the generator to continuously supply power even at 25% load variation whereas generator with PID based governor fails to supply power even at 20% load variation.
Keywords: Mini hydro, fuzzy based governor, PID based governor, distribution network
DOI: 10.3233/IFS-130816
Journal: Journal of Intelligent & Fuzzy Systems, vol. 26, no. 3, pp. 1301-1310, 2014
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