Improved Restricted Control Set Model Predictive Control (iRCS-MPC) Based Maximum Power Point Tracking of Photovoltaic Module

This paper presents a robust two stage maximum power point tracking (MPPT) system of the photovoltaic (PV) module using an improved restricted control set model predictive control (iRCS-MPC) technique. The suggested work is improved in two aspects; a revision in conventional P&O algorithm is made by employing three distinct step sizes for different conditions, and an improvement in conventional MPC algorithm. The improved MPC algorithm is based on the single step prediction horizon that provides less computational load and swift tracking of maximum power point (MPP) by applying the control pulses directly to the converter switch. The computer aided experimental results for various environmental scenarios revealed that compared with the conventional method (conventional P&O + MPC), for the PV power and inductor current, the undershoot and overshoot is decreased to 68% and 35% respectively under stiff environmental conditions. In addition, the settling time needed to reach a stable state is significantly reduced in the proposed system. The viability of the solution suggested is verified in MATLAB/Simulink and by hardware experimentation.

[1]  Z. Salam,et al.  An improved perturb and observe (P&O) maximum power point tracking (MPPT) algorithm for higher efficiency , 2015 .

[2]  E. Tissir,et al.  Achievement of MPPT by finite time convergence sliding mode control for photovoltaic pumping system , 2018 .

[3]  Luigi Piegari,et al.  Optimized Adaptive Perturb and Observe Maximum Power Point Tracking Control for Photovoltaic Generation , 2015 .

[4]  Kok Soon Tey,et al.  Modified incremental conductance MPPT algorithm to mitigate inaccurate responses under fast-changing solar irradiation level , 2014 .

[5]  Huiqing Wen,et al.  A novel beta parameter based fuzzy-logic controller for photovoltaic MPPT application , 2019, Renewable Energy.

[6]  Robert S. Balog,et al.  Model Predictive Control of PV Sources in a Smart DC Distribution System: Maximum Power Point Tracking and Droop Control , 2014, IEEE Transactions on Energy Conversion.

[7]  Ahmad Saudi Samosir,et al.  Modeling and Simulation of Fuzzy Logic based Maximum Power Point Tracking (MPPT) for PV Application , 2018, International Journal of Electrical and Computer Engineering (IJECE).

[8]  Hegazy Rezk,et al.  Optimal parameter design of fractional order control based INC-MPPT for PV system , 2018 .

[9]  Abdelghani Harrag,et al.  Variable step size modified P&O MPPT algorithm using GA-based hybrid offline/online PID controller , 2015 .

[10]  Rached Dhaouadi,et al.  Efficiency Optimization of a DSP-Based Standalone PV System Using Fuzzy Logic and Dual-MPPT Control , 2012, IEEE Transactions on Industrial Informatics.

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

[12]  Carlos A. Canesin,et al.  Evaluation of the Main MPPT Techniques for Photovoltaic Applications , 2013, IEEE Transactions on Industrial Electronics.

[13]  D. Baimel,et al.  Novel optimized method for maximum power point tracking in PV systems using Fractional Open Circuit Voltage technique , 2016, 2016 International Symposium on Power Electronics, Electrical Drives, Automation and Motion (SPEEDAM).

[14]  Mazen Abdel-Salam,et al.  An improved perturb-and-observe based MPPT method for PV systems under varying irradiation levels , 2018, Solar Energy.

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

[16]  M. Arutchelvi,et al.  Analysis and enhancement of PV efficiency with incremental conductance MPPT technique under non-linear loading conditions , 2015 .

[17]  S. K. Kollimalla,et al.  A Novel Adaptive P&O MPPT Algorithm Considering Sudden Changes in the Irradiance , 2014, IEEE Transactions on Energy Conversion.

[18]  Marcello Chiaberge,et al.  An intelligent control strategy of fractional short circuit current maximum power point tracking technique for photovoltaic applications , 2015 .

[19]  Antonios G. Kladas,et al.  Implementation of photovoltaic array MPPT through fixed step predictive control technique , 2011 .

[20]  B. Zahawi,et al.  Assessment of Perturb and Observe MPPT Algorithm Implementation Techniques for PV Pumping Applications , 2012, IEEE Transactions on Sustainable Energy.

[21]  Barry W. Williams,et al.  Improved performance low-cost incremental conductance PV MPPT technique , 2016 .

[22]  A. J. Sguarezi Filho,et al.  Constant switching frequency finite control set model predictive control applied to the boost converter of a photovoltaic system , 2019 .

[23]  Osama A. Mohammed,et al.  Design and Hardware Implementation of FL-MPPT Control of PV Systems Based on GA and Small-Signal Analysis , 2017, IEEE Transactions on Sustainable Energy.

[24]  Ali Faisal Murtaza,et al.  Power tracking techniques for efficient operation of photovoltaic array in solar applications – A review , 2019, Renewable and Sustainable Energy Reviews.

[25]  Marcello Chiaberge,et al.  A New Sensorless Hybrid MPPT Algorithm Based on Fractional Short-Circuit Current Measurement and P&O MPPT , 2015, IEEE Transactions on Sustainable Energy.

[26]  Tsung-Wei Hsu,et al.  Photovoltaic Energy Harvester With Fractional Open-Circuit Voltage Based Maximum Power Point Tracking Circuit , 2019, IEEE Transactions on Circuits and Systems II: Express Briefs.

[27]  Kamal Al-Haddad,et al.  An Efficient and Cost-Effective Hybrid MPPT Method for a Photovoltaic Flyback Microinverter , 2018, IEEE Transactions on Sustainable Energy.