A hybrid intelligent GMPPT algorithm for partial shading PV system

Abstract Maximum power extraction for PV systems under partial shading conditions (PSCs) relies on the optimal global maximum power point tracking (GMPPT) method used. This paper proposes a novel maximum power point tracking (MPPT) control method for PV system with reduced steady-state oscillation based on improved particle swarm optimization (PSO) algorithm and variable step perturb and observe (P&O) method. Firstly, the grouping idea of shuffled frog leaping algorithm (SFLA) is introduced in the basic PSO algorithm (PSO–SFLA), ensuring the differences among particles and the searching of global extremum. Furthermore, adaptive speed factor is introduced into the improved PSO to improve the convergence of the PSO–SFLA under PSCs. And then, the variable step P&O (VSP&O) method is used to track the maximum power point (MPP) accurately with the change of environment. Finally, the superiority of the proposed method over the conventional P&O method and the standard PSO method in terms of tracking speed and steady-state oscillations is highlighted by simulation results under fast variable PSCs.

[1]  Soteris A. Kalogirou,et al.  Maximum power point tracking using a GA optimized fuzzy logic controller and its FPGA implementation , 2011 .

[2]  Saad Mekhilef,et al.  Simulation and Hardware Implementation of Incremental Conductance MPPT With Direct Control Method Using Cuk Converter , 2011, IEEE Transactions on Industrial Electronics.

[3]  Chakkarapani Manickam,et al.  A Hybrid Algorithm for Tracking of GMPP Based on P&O and PSO With Reduced Power Oscillation in String Inverters , 2016, IEEE Transactions on Industrial Electronics.

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

[5]  Kashif Ishaque,et al.  An Improved Particle Swarm Optimization (PSO)–Based MPPT for PV With Reduced Steady-State Oscillation , 2012, IEEE Transactions on Power Electronics.

[6]  Kevin E Lansey,et al.  Optimization of Water Distribution Network Design Using the Shuffled Frog Leaping Algorithm , 2003 .

[7]  Fouad Giri,et al.  Climatic sensorless maximum power point tracking in PV generation systems , 2011 .

[8]  Sabir Messalti,et al.  Simulation and experimental design of a new advanced variable step size Incremental Conductance MPPT algorithm for PV systems. , 2016, ISA transactions.

[9]  Yi-Hua Liu,et al.  Optimization of a Fuzzy-Logic-Control-Based MPPT Algorithm Using the Particle Swarm Optimization Technique , 2015 .

[10]  Pan Duan,et al.  Comprehensive improvement of artificial fish swarm algorithm for global MPPT in PV system under partial shading conditions , 2018, Trans. Inst. Meas. Control.

[11]  S. Jeevananthan,et al.  A new maximum power tracking in PV system during partially shaded conditions based on shuffled frog leap algorithm , 2017, J. Exp. Theor. Artif. Intell..

[12]  L. Zhang,et al.  On-line neural network training for maximum power point tracking of PV power plant , 2008 .

[13]  Pan Duan,et al.  An Improved Variable Step PO and Global Scanning MPPT Method for PV Systems under Partial Shading Condition , 2015, 2015 7th International Conference on Intelligent Human-Machine Systems and Cybernetics.

[14]  Sishaj P. Simon,et al.  Maximum Power Point Tracking of Photovoltaic Generation System using Artificial Neural Network with Improved Tracking Factor , 2014 .

[15]  Karima Benatchba,et al.  A new MPPT controller based on the Ant colony optimization algorithm for Photovoltaic systems under partial shading conditions , 2017, Appl. Soft Comput..

[16]  Awang Jusoh,et al.  Modified Perturb and Observe (P&O) with checking algorithm under various solar irradiation , 2017 .

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

[18]  B N Alajmi,et al.  Fuzzy-Logic-Control Approach of a Modified Hill-Climbing Method for Maximum Power Point in Microgrid Standalone Photovoltaic System , 2011, IEEE Transactions on Power Electronics.

[19]  Chee Wei Tan,et al.  Photovoltaic Multiple Peaks Power Tracking Using Particle Swarm Optimization with Artificial Neural Network Algorithm , 2016 .

[20]  J. W. Bishop.  Computer simulation of the effects of electrical mismatches in photovoltaic cell interconnection circuits , 1988 .

[21]  S. M. Abd-Elazim,et al.  PI controller design using ABC algorithm for MPPT of PV system supplying DC motor pump load , 2017, Neural Computing and Applications.

[22]  Chakkarapani Manickam,et al.  Fireworks Enriched P&O Algorithm for GMPPT and Detection of Partial Shading in PV Systems , 2017, IEEE Transactions on Power Electronics.

[23]  Vanxay Phimmasone,et al.  Evaluation of extracted energy from PV with PSO-based MPPT against various types of solar irradiation changes , 2010, 2010 International Conference on Electrical Machines and Systems.

[24]  Miroslav Krstic,et al.  Multivariable maximum power point tracking for photovoltaic micro-converters using extremum seeking , 2015 .

[25]  Zegrari Mourad,et al.  An advanced MPPT based on Artificial Bee Colony Algorithm for MPPT photovoltaic system under partial shading Condition , 2017 .

[26]  M. Vitelli,et al.  Optimization of perturb and observe maximum power point tracking method , 2005, IEEE Transactions on Power Electronics.