TY - JOUR
T1 - Optimal power tracking of PMSG based wind energy conversion systems by constrained direct control with fast convergence rates
AU - The Nguyen, Hoach
AU - Al-Sumaiti, Ameena Saad
AU - Vu, Van Phong
AU - Al-Durra, Ahmed
AU - Do, Ton Duc
N1 - Funding Information:
This work was supported by Khalifa University, Abu Dhabi, United Arab Emirates under Award No. FSU-2018-25. This work was also supported by Nazarbayev University, Kazakhstan under the NU-ORAU Program, award no. SST2017030.
Funding Information:
This work was supported by Khalifa University, Abu Dhabi, United Arab Emirates under Award No. FSU-2018-25 . This work was also supported by Nazarbayev University , Kazakhstan under the NU-ORAU Program, award no. SST2017030 . Appendix A
Publisher Copyright:
© 2019 Elsevier Ltd
PY - 2020/6
Y1 - 2020/6
N2 - This paper proposes a simple direct control with fast convergence rates under constraints for tracking optimal power of permanent magnet synchronous generator (PMSG) based wind energy conversion system (WECS). The simplicity features are on neglecting the following: predicted control performances, measurement of aerodynamic torque/wind speed and stator currents. The superior features are on very fast and accurate tracking performances with asymptotic convergence and well-regulated stator currents. First, a nonlinear observer is designed to observe both aerodynamic torque and stator currents. The wind speed is then inferred from the estimated aerodynamic torque and consequently, the optimal speed reference is identified. Next, the conditions of asymptotic stability for the closed-loop dynamics are formulated. Finally, a simple direct control is proposed to maximize the convergence rates in transient states and reduce switching frequency in steady states. Comparative studies with finite set model predictive control are presented to validate the advantageous features of the proposed method. The comparative results show that the superiority of the proposed method is proved by better controlled outputs with lower ripples, smaller steady-state tracking errors, faster response in transient-states, good tracking performance even for fast-varying aerodynamic torque, and lower average switching-frequency.
AB - This paper proposes a simple direct control with fast convergence rates under constraints for tracking optimal power of permanent magnet synchronous generator (PMSG) based wind energy conversion system (WECS). The simplicity features are on neglecting the following: predicted control performances, measurement of aerodynamic torque/wind speed and stator currents. The superior features are on very fast and accurate tracking performances with asymptotic convergence and well-regulated stator currents. First, a nonlinear observer is designed to observe both aerodynamic torque and stator currents. The wind speed is then inferred from the estimated aerodynamic torque and consequently, the optimal speed reference is identified. Next, the conditions of asymptotic stability for the closed-loop dynamics are formulated. Finally, a simple direct control is proposed to maximize the convergence rates in transient states and reduce switching frequency in steady states. Comparative studies with finite set model predictive control are presented to validate the advantageous features of the proposed method. The comparative results show that the superiority of the proposed method is proved by better controlled outputs with lower ripples, smaller steady-state tracking errors, faster response in transient-states, good tracking performance even for fast-varying aerodynamic torque, and lower average switching-frequency.
KW - Asymptotic stability (A.S)
KW - Direct control
KW - Finite control set model predictive control (FCS-MPC)
KW - Nonlinear observer
KW - Permanent magnet synchronous generator (PMSG)
KW - Wind turbine
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U2 - 10.1016/j.ijepes.2019.105807
DO - 10.1016/j.ijepes.2019.105807
M3 - Article
AN - SCOPUS:85077202849
SN - 0142-0615
VL - 118
JO - International Journal of Electrical Power and Energy Systems
JF - International Journal of Electrical Power and Energy Systems
M1 - 105807
ER -