Adaptive Fuzzy-PI Control of Wind Energy Conversion System Based DFIG under Voltage Dip

TitreAdaptive Fuzzy-PI Control of Wind Energy Conversion System Based DFIG under Voltage Dip
Publication TypeConference Paper
Year of Publication2020
AuthorsKharchouf, I, Nasser, T, Essadki, A, Fdaili, M
Conference Name2020 International Conference on Electrical and Information Technologies, ICEIT 2020
Mots-clésAdaptive control systems, Adaptive fuzzy-PI control, Asynchronous generators, Control methodology, Controllers, Doubly fed induction generators, Electric fault currents, Electric machine control, Energy conversion, Fuzzy logic, Fuzzy logic controllers, MATLAB, Power control, Proportional integral, Two term control systems, Variable speed wind energy conversion systems, Water craft, Wind, Wind energy conversion system, Wind power, Wind speed variations
Abstract

The Proportional-Integral (PI) and Fuzzy Logic Controllers (FLC) cannot deal accurately with the system variation. To overcome the drawbacks of PI and FLC regulators, the Adaptive Fuzzy-PI Controllers (AFPICs) are configured. This paper presents a comparison between three different controllers based control methodology for Variable Speed Wind Energy Conversion Systems (WECSs) by means of Doubly Fed Induction Generator (DFIG). Artificial Intelligence (AI) based FLCs is performed to improve the system efficiency and performance under Small Disturbance (SD) and Large Disturbance (LD) cases. To test the PI, FLC, and AFPIC robustness, simulations are done during abrupt wind speed variation (SD), and voltage dip fault (LD). The simulation results show that the proposed AFPIC delivers improved power control, better response rise time, reduced overshoot, undershoot, and settling time compared to classical PI and Fuzzy controllers. The proposed control is proved by simulation using Matlab/Simulink-R2016b. © 2020 IEEE.

URLhttps://www.scopus.com/inward/record.uri?eid=2-s2.0-85086889728&doi=10.1109%2fICEIT48248.2020.9113215&partnerID=40&md5=514df1b642398d6a25a07b76a59427bf
DOI10.1109/ICEIT48248.2020.9113215
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