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Direct Power Control of Dfig by Using Nonlinear Model Predictive Controller
Author(s) -
Kalamian Nasrin,
Verij Kazemi Mohammad,
Gholomian S. Asghar
Publication year - 2016
Publication title -
asian journal of control
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.769
H-Index - 53
eISSN - 1934-6093
pISSN - 1561-8625
DOI - 10.1002/asjc.1170
Subject(s) - control theory (sociology) , nonlinear model , doubly fed electric machine , nonlinear system , controller (irrigation) , model predictive control , control engineering , power (physics) , control (management) , computer science , engineering , ac power , artificial intelligence , physics , biology , quantum mechanics , agronomy
This paper proposes a nonlinear model predictive direct power control (PDPC) strategy for a double fed induction generator (DFIG)‐based wind energy generation system. Active and reactive power variations of DFIG are calculated based on machine rules, and a nonlinear model of DFIG is given. A nonlinear model predictive controller (NMPC) is presented based on the useful cost function and constraint that it results in more proximity between simulations and reality. The power and current ripples are reduced and the optimal rotor voltage is generated based on an objective function and the constraints. The rotor voltage vector is calculated in the synchronous reference frame and transferred into the rotor reference frame. Simulation results of a 2 MW DFIG system show good performance of the proposed method during variation of active and reactive powers, machine parameters, and wind speed. Also, the transient responses of active and reactive powers are within a few milliseconds.