Implementation of Incremental Conductance Based MPPT Algorithm for Photovoltaic System

This paper deals with the hardware implementation of incremental conductance (IncCond) algorithm based maximum power point tracking (MPPT) for a photovoltaic (PV) system using Arduino board. The considered system consists of a DC-DC Boost converter, a PV panel and a resistive load. Firstly, simulation tests using Matlab/Siumilink are provided and then experimental validation is conduced based on an Arduino uno and spatial Simulink package known as "support package for Arduino hardware". The simulation and experimental tests show the satisfied results of IncCond algorithm in terms of extraction of the maximum power point(MPP) form PV panel.

[1]  Houria Boumaaraf,et al.  A three-phase NPC grid-connected inverter for photovoltaic applications using neural network MPPT , 2015 .

[2]  Yu-Pei Huang,et al.  A performance evaluation model of a high concentration photovoltaic module with a fractional open circuit voltage-based maximum power point tracking algorithm , 2016, Comput. Electr. Eng..

[3]  Yie-Tone Chen,et al.  A fuzzy-logic based auto-scaling variable step-size MPPT method for PV systems , 2016 .

[4]  P. Vivek,et al.  A novel approach on MPPT algorithm for solar panel using buck boost converter , 2016, 2016 International Conference on Energy Efficient Technologies for Sustainability (ICEETS).

[5]  Zeeshan Mehmood,et al.  Implementation of the novel temperature controller and incremental conductance MPPT algorithm for indoor photovoltaic system , 2018 .

[6]  Kai Strunz,et al.  Efficient Digital Control for MPP Tracking and Output Voltage Regulation of Partially Shaded PV Modules in DC Bus and DC Microgrid Systems , 2019, IEEE Transactions on Power Electronics.

[7]  Adel Mellit,et al.  Applications of Improved Versions of Fuzzy Logic Based Maximum Power Point Tracking for Controlling Photovoltaic Systems , 2019, Power Systems.

[8]  Yi-Hua Liu,et al.  An Asymmetrical Fuzzy-Logic-Control-Based MPPT Algorithm for Photovoltaic Systems , 2014 .

[9]  Saad Mekhilef,et al.  Implementation of a modified incremental conductance MPPT algorithm with direct control based on a fuzzy duty cycle change estimator using dSPACE , 2014 .

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

[11]  Prabhakar Tiwari,et al.  Smart Switching Algorithm Between IC and PO Algorithms for Grid-Connected PV System , 2018 .

[12]  D. Ounnas,et al.  Tracking control for permanent magnet synchronous machine based on Takagi-Sugeno fuzzy models , 2013, 2013 Eighth International Conference and Exhibition on Ecological Vehicles and Renewable Energies (EVER).

[13]  Abdelghani Harrag,et al.  A new variable step size neural networks MPPT controller: Review, simulation and hardware implementation , 2017 .

[14]  Matthew W. Dunnigan,et al.  Development and Comparison of an Improved Incremental Conductance Algorithm for Tracking the MPP of a Solar PV Panel , 2016, IEEE Transactions on Sustainable Energy.

[15]  B. W. Williams,et al.  Modified variable-step incremental conductance maximum power point tracking technique for photovoltaic systems , 2013, IECON 2013 - 39th Annual Conference of the IEEE Industrial Electronics Society.

[16]  Ahmed Fathy,et al.  Simulation of global MPPT based on teaching–learning-based optimization technique for partially shaded PV system , 2017 .

[17]  Leopoldo G. Franquelo,et al.  Grid-Connected Photovoltaic Systems: An Overview of Recent Research and Emerging PV Converter Technology , 2015, IEEE Industrial Electronics Magazine.

[18]  Xiaoli Meng,et al.  A review of maximum power point tracking methods of PV power system at uniform and partial shading , 2016 .

[19]  T. Bouktir,et al.  An Efficient Maximum Power Point Tracking Controller for Photovoltaic Systems Using Takagi–Sugeno Fuzzy Models , 2017 .

[20]  Abhinandan Jain,et al.  Hardware Implementation of Perturb and Observe Maximum Power Point Tracking Algorithm for Solar Photovoltaic System , 2018, Transactions on Electrical and Electronic Materials.

[21]  Prakash Kumar,et al.  Genetic algorithm based maximum power tracking in solar power generation , 2015, 2015 International Conference on Power and Advanced Control Engineering (ICPACE).