Publication: ANFIS based neuro-fuzzy control of dfig for wind power generation in standalone mode
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Date
2019
Authors
Amin I.K.
Nasir Uddin M.
Marsadek M.
Journal Title
Journal ISSN
Volume Title
Publisher
Institute of Electrical and Electronics Engineers Inc.
Abstract
This paper presents an adaptive neuro-fuzzy controller (NFC)for doubly fed induction generator (DFIG)based wind energy conversion system (WECS)to operate under standalone mode. The NFC is developed based on adaptive-network-based fuzzy inference system (ANFIS)architecture since it has the unique advantage of fast convergence combining the robustness of fuzzy logic and flexibility of neural network algorithm. For the isolated operation of DFIG-WECS, ANFIS is designed for load side converter (LSC)control. The proposed scheme demonstrates improved dynamic performance under variable wind speed and load conditions by maintaining stable output voltage. The supply frequency to the load remains stable by virtue of precise control of LSC while turbine rotation varies with fluctuating wind speed. The flux alignment is ensured by the proportional-integral (PI)control of rotor side converter. The simulation results exhibit the controller's outstanding performance through its robust control over load-voltage and supply frequency under the variation of demand load power and wind speed. � 2019 IEEE.
Description
Adaptive control systems; Asynchronous generators; Controllers; Electric drives; Electric fault currents; Electric power generation; Fuzzy control; Fuzzy inference; Fuzzy logic; Fuzzy neural networks; Inference engines; Robust control; Two term control systems; Wind; Wind power; Adaptive network based fuzzy inference system; Doubly fed induction generator (DFIG); Doubly fed induction generators; Neural network algorithm; Neuro-fuzzy controller; Proportional-integral control; Stand-alone modes; Wind energy conversion system; Electric machine control