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Appl. Sci. 2018, 8(3), 373; doi:10.3390/app8030373

Hybrid Genetic Algorithm Fuzzy-Based Control Schemes for Small Power System with High-Penetration Wind Farms

1
Department of Electrical Power and Machines, Zagazig University, Zagazig 44519, Egypt
2
Department of Electrical and Electronics Engineering, University of the Ryukyus, Okinawa 903-0213, Japan
3
Department of Electrical and Biomedical Engineering, RMIT University, Melbourne, Victoria 3001, Australia
*
Author to whom correspondence should be addressed.
Received: 2 February 2018 / Revised: 21 February 2018 / Accepted: 1 March 2018 / Published: 4 March 2018
(This article belongs to the Special Issue Renewable Energy 2018)
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Simple Summary

This paper can be considered as a complete study clarifying the impact of implementing high-penetration renewable energy sources in small power systems from the frequency and active power points of view

Abstract

Wind is a clean, abundant, and inexhaustible source of energy. However, wind power is not constant, as windmill output is proportional to the cube of wind speed. As a result, the generated power of wind turbine generators (WTGs) fluctuates significantly. Power fluctuation leads to frequency deviation and voltage flicker inside the system. This paper presents a new methodology for controlling system frequency and power. Two decentralized fuzzy logic-based control schemes with a high-penetration non-storage wind–diesel system are studied. First, one is implemented in the governor of conventional generators to damp frequency oscillation, while the other is applied to control the pitch angle system of wind turbines to smooth wind output power fluctuations and enhance the power system performance. A genetic algorithm (GA) is employed to tune and optimize the membership function parameters of the fuzzy logic controllers to obtain optimal performance. The effectiveness of the suggested controllers is validated by time domain simulation for the standard IEEE nine-bus three-generator test system, including three wind farms. The robustness of the power system is checked under normal and faulty operating conditions. View Full-Text
Keywords: fuzzy control; frequency control; genetic algorithm; pitch angle control; power system stability; wind power generation fuzzy control; frequency control; genetic algorithm; pitch angle control; power system stability; wind power generation
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Lotfy, M.E.; Senjyu, T.; Farahat, M.A.-F.; Abdel-Gawad, A.F.; Lei, L.; Datta, M. Hybrid Genetic Algorithm Fuzzy-Based Control Schemes for Small Power System with High-Penetration Wind Farms. Appl. Sci. 2018, 8, 373.

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