MPPT strategy based on speed control for AWS-based wave energy conversion system

One of the attractive direct-drive wave energy conversion systems is the Archimedes Wave Swing (AWS) coupled to a Linear Permanent Magnet Synchronous Generator (LPMSG). This paper presents an integrated control strategy for the back-to-back converter interfacing the LPMSG not only to extract the maximum power from the wave, but also to ride-through the fault. The proposed maximum power tracking technique is based on speed sensorless control of the LPMSG. The unscented Kalman filter is adapted to estimate the translator velocity. The optimal velocity is obtained from the instantaneous active power at the generator terminals. Moreover, a low-voltage ride-through control is integrated to satisfy the grid-code requirements by injecting reactive current during grid disturbances. The generated active power at the fault instant is considered in determining the dynamic reactive power injection to not exceed the ratings of the grid-side converter. The superiority of the proposed strategy is the result of its ability to regulate the translator velocity that generates optimum power. Numerical simulations are conducted to evaluate the dynamic performance of the proposed integrated optimal strategy. Besides, it has been shown that the proposed methodology outdoes others by the decreased power fluctuations which leads to a reduction of the converter size.

[1]  E. Muljadi,et al.  Making connections [wind generation facilities] , 2005, IEEE Power and Energy Magazine.

[2]  M. Molinas,et al.  Power electronics as grid interface for actively controlled wave energy converters , 2007, 2007 International Conference on Clean Electrical Power.

[3]  Weimin Wang,et al.  Application of Unscented Kalman filter to sensorless permanent-magnet synchronous motor drive , 2009, 2009 IEEE International Electric Machines and Drives Conference.

[4]  D.L. O'Sullivan,et al.  Generator selection for offshore oscillating water column wave energy converters , 2008, 2008 13th International Power Electronics and Motion Control Conference.

[5]  Xiaobin Li,et al.  Position Sensorless Control for PMLSM Using Elman Neural Network , 2009, 2009 International Conference on Information Engineering and Computer Science.

[6]  T. K. A. Brekken,et al.  Maximum Power Point Tracking for Ocean Wave Energy Conversion , 2012, IEEE Transactions on Industry Applications.

[7]  Xiaoxin Wang,et al.  Speed sensorless control of a linear synchronous motor using state observer on d-q reference frame , 2008, 2008 International Conference on Electrical Machines and Systems.

[8]  Ross Henderson,et al.  Design, simulation, and testing of a novel hydraulic power take-off system for the Pelamis wave energy converter , 2006 .

[9]  Rudolph van der Merwe,et al.  The unscented Kalman filter for nonlinear estimation , 2000, Proceedings of the IEEE 2000 Adaptive Systems for Signal Processing, Communications, and Control Symposium (Cat. No.00EX373).

[10]  P.F.A. MacConnell,et al.  A novel MRAS current-based sensorless vector controlled PMLSM drive for low speed operation , 2003, IEEE International Electric Machines and Drives Conference, 2003. IEMDC'03..

[11]  J. Sa da Costa,et al.  Modeling of an ocean waves power device AWS , 2003, Proceedings of 2003 IEEE Conference on Control Applications, 2003. CCA 2003..

[12]  Izaskun Garrido Hernandez,et al.  Fault-Ride-Through Capability of Oscillating-Water-Column-Based Wave-Power-Generation Plants Equipped With Doubly Fed Induction Generator and Airflow Control , 2011, IEEE Transactions on Industrial Electronics.

[13]  H. Polinder,et al.  Linear PM Generator system for wave energy conversion in the AWS , 2004, IEEE Transactions on Energy Conversion.

[14]  Gianmario Pellegrino,et al.  End Effects in Linear Tubular Motors and Compensated Position Sensorless Control Based on Pulsating Voltage Injection , 2011, IEEE Transactions on Industrial Electronics.

[15]  Jonathan Shek,et al.  Reaction force control of a linear electrical generator for direct drive wave energy conversion , 2007 .

[16]  Mats Leijon,et al.  Review on electrical control strategies for wave energy converting systems , 2014 .

[17]  Jeffrey K. Uhlmann,et al.  Unscented filtering and nonlinear estimation , 2004, Proceedings of the IEEE.

[18]  Markus Mueller,et al.  Power Conditioning of the Output from a Linear Vernier Hybrid Permanent Magnet Generator for using Direct Drive Wave Energy Converters , 2005 .

[19]  Jon Andreu,et al.  Review of wave energy technologies and the necessary power-equipment , 2013 .

[20]  Aitor J. Garrido,et al.  Neural control for voltage dips ride-through of oscillating water column-based wave energy converter equipped with doubly-fed induction generator , 2012 .

[21]  Xiao-Ping Zhang,et al.  Modeling, Control Strategy, and Power Conditioning for Direct-Drive Wave Energy Conversion to Operate With Power Grid , 2013, Proceedings of the IEEE.

[22]  Peter Frigaard,et al.  Prototype Testing of the Wave Energy Converter Wave Dragon , 2006 .

[23]  E. Kerrigan,et al.  Optimal Active Control and Optimization of a Wave Energy Converter , 2013, IEEE Transactions on Sustainable Energy.

[24]  Xiao-Ping Zhang,et al.  Modeling and Control of AWS-Based Wave Energy Conversion System Integrated Into Power Grid , 2008, IEEE Transactions on Power Systems.

[25]  Peter Tavner,et al.  Power conversion and control for a linear direct drive permanent magnet generator for wave energy , 2011 .

[26]  Norbert C. Cheung,et al.  Sensorless drive of permanent magnet linear motors using modified Kalman filter , 2001, 2001 IEEE 32nd Annual Power Electronics Specialists Conference (IEEE Cat. No.01CH37230).

[27]  Richard R. Gaillardetz,et al.  Making the Connections , 2002 .