Effects and compensations of computational delay in finite set-model predictive control in renewable energy system

This paper focuses on the model predictive current control of power converters with the aim of indicating the influence of some system parameters used in predictive control on the load current and load voltage. A model predictive current control algorithm is proposed, specifically directed at the utilization of power obtained from renewable energy systems (RESs). In this study the renewable energy systems model is used to investigate system performance when power is supplied to a resistive-inductive load (RL-load). A finite set-model predictive current control (FS-MPCC) method is developed to control the output current of three-phase, voltage source inverter (VSI). The approximation methods for the derivatives of the model differential equations and delay compensation of model predictive control (MPC) system for power converters are assessed. Simulation results of a two-level, three-phase VSI using FS-MPCC are carried out to show the effects of different approximation methods on the load current and voltage regulation as well as on the predictive current control operation with and without delay compensation for different sampling times. It has been noticed that the ripple in the load currents is considerable when the delay compensation is not accounted for and the delay compensation method that reduces the ripple and operation is similar to the ideal case. It is confirmed that for larger sampling times the delay is noticeable, but when the sampling time is smaller it is not visible.

[1]  Dennis G. Zill,et al.  Advanced Engineering Mathematics , 2021, Technometrics.

[2]  José R. Rodríguez,et al.  Predictive Torque Control of Induction Machines Based on State-Space Models , 2009, IEEE Transactions on Industrial Electronics.

[3]  Stefan Müller,et al.  New time-discrete modulation scheme for matrix converters , 2005, IEEE Transactions on Industrial Electronics.

[4]  Jorge Pontt,et al.  Predictive Control of a Three-Phase Neutral-Point-Clamped Inverter , 2007, IEEE Transactions on Industrial Electronics.

[5]  Haitham Abu-Rub,et al.  Predictive current control of voltage-source inverters , 2004, IEEE Transactions on Industrial Electronics.

[6]  F. Blaabjerg,et al.  An integral space-vector PWM technique for DSP-controlled voltage-source inverters , 1998, Conference Record of 1998 IEEE Industry Applications Conference. Thirty-Third IAS Annual Meeting (Cat. No.98CH36242).

[7]  G.S. Perantzakis,et al.  Efficient predictive current control technique for multilevel voltage source inverters , 2005, 2005 European Conference on Power Electronics and Applications.

[8]  A. Purcell,et al.  Multilevel hysteresis comparator forms for direct torque control schemes , 1998 .

[9]  Ralph Kennel,et al.  Predictive control in power electronics and drives , 2008, 2008 IEEE International Symposium on Industrial Electronics.

[10]  R. S. Kanchan,et al.  Model-Based Predictive Control of Electric Drives , 2010 .

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

[12]  Patricio Cortes,et al.  Predictive Control of Power Converters and Electrical Drives: Rodriguez/Predictive Control of Power Converters and Electrical Drives , 2012 .

[13]  P. Wheeler,et al.  Predective Control Strategy for ZCS Single Stage Resonant Converter , 2006, IECON 2006 - 32nd Annual Conference on IEEE Industrial Electronics.

[14]  Jan M. Maciejowski,et al.  Predictive control : with constraints , 2002 .

[15]  J. A. Rossiter,et al.  Model-Based Predictive Control : A Practical Approach , 2017 .

[16]  Marko Bacic,et al.  Model predictive control , 2003 .