A Model Predictive Control for Maximum Power Point Tracking of Wind Energy Conversion Systems

In this paper, Maximum Power Point Tracking control(MPPT) of wind Energy Conversion Systems (WECSs) is studied and a new method based on Model Predictive Control(MPC) is proposed. In this method, the discrete linear time-invariant state space equation of WECSs is used as prediction model, the objectives function of the rolling optimization is designed to penalize the deviation between the reference trajectory and controlled output and the KALMAN filter is used to design the state observer. Compared with the traditional control method, the new method has good characteristics on reducing the error of the model's uncertainty. Simulation system is designed in the MATLAB, MPC controller and other traditional controllers are compared, the simulation results show that the proposed method has good robustness and high efficiency.

[1]  Volker Pickert,et al.  Overview of maximum power point tracking control methods for PV systems , 2014 .

[2]  Marian P. Kazmierkowski,et al.  State of the Art of Finite Control Set Model Predictive Control in Power Electronics , 2013, IEEE Transactions on Industrial Informatics.

[3]  Andres Barrado,et al.  Review of the maximum power point tracking algorithms for stand-alone photovoltaic systems , 2006 .

[4]  Pablo Lezana,et al.  Predictive Current Control of a Voltage Source Inverter , 2004, IEEE Transactions on Industrial Electronics.

[5]  David T. Westwick,et al.  Multiple model multiple-input multiple-output predictive control for variable speed variable pitch wind energy conversion systems , 2011 .

[6]  Shao Zhang,et al.  Design of a Robust Grid Interface System for PMSG-Based Wind Turbine Generators , 2011, IEEE Transactions on Industrial Electronics.

[7]  Ji Zhicheng,et al.  Modeling and MPPT control of squirrel-cage induction generator wind power generation system via VisSim , 2009, 2009 Chinese Control and Decision Conference.

[8]  Shuhui Li,et al.  Optimal and Direct-Current Vector Control of Direct-Driven PMSG Wind Turbines , 2012, IEEE Transactions on Power Electronics.

[9]  V. T. Ranganathan,et al.  A Method of Tracking the Peak Power Points for a Variable Speed Wind Energy Conversion System , 2002, IEEE Power Engineering Review.

[10]  F. L. Tofoli,et al.  Comparative Study of Maximum Power Point Tracking Techniques for Photovoltaic Systems , 2015 .

[11]  Francisco A. S. Neves,et al.  Comparative Study Of Maximum Power Point Tracking Techniques For Photovoltaic Systems , 2007 .

[12]  Yunjie Gu,et al.  Mode-Adaptive Decentralized Control for Renewable DC Microgrid With Enhanced Reliability and Flexibility , 2014, IEEE Transactions on Power Electronics.

[13]  Sathish Kumar Kollimalla,et al.  Comparitive study of P&O and incremental conductance method for PV system , 2017, 2017 International Conference on Circuit ,Power and Computing Technologies (ICCPCT).

[14]  Myung-Joong Youn,et al.  New Maximum Power Point Tracker Using Sliding-Mode Observer for Estimation of Solar Array Current in the Grid-Connected Photovoltaic System , 2006, IEEE Transactions on Industrial Electronics.

[15]  Zhigang Chen,et al.  A novel fuzzy logic and anti-windup PI controller for a rectifier with direct driven permanent magnet synchronous generator , 2009, 2009 2nd International Conference on Power Electronics and Intelligent Transportation System (PEITS).

[16]  Yang Xiyun.  A Study on Dynamic Optimal Control Strategy for Large-scale Wind Power Generation System , 2010 .

[17]  Li Zhi,et al.  An Ultra-short-term Wind Power Forecasting Method in Regional Grids , 2010 .

[18]  Jan Melkebeek,et al.  Analysis of some design choices in model based predictive control of flying‐capacitor inverters , 2012 .