A novel photovoltaic maximum power point tracking technique based on grasshopper optimized fuzzy logic approach

Abstract The maximum power point tracking (MPPT) in the PV system has become complex due to the stochastic nature of the load, intermittency in solar irradiance and ambient temperature. To address this problem, a novel Grasshopper optimized fuzzy logic control (FLC) approach based MPPT technique is proposed in this paper. In this proposed MPPT, grasshopper optimization is used to tune the membership functions (MFs) of FLC to handle all uncertainties caused by variable irradiances and temperatures. The performance of the proposed grasshopper optimized FLC based MPPT is studied under rapidly changing irradiance and temperature. The proposed MPPT overcomes the limitations such as slow convergence speed, steady-state oscillations, lower tracking efficiency as encountered in conventional methods viz. perturb & observed (P&O) and FLC techniques. The feasibility of the proposed MPPT is validated through experimentation. The effectiveness of the proposed scheme is compared with P&O and also with FLC MPPT.

[1]  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.

[2]  Nasrudin Abd Rahim,et al.  A review on global solar energy policy , 2011 .

[3]  M. Seyedmahmoudian,et al.  Simulation and Hardware Implementation of New Maximum Power Point Tracking Technique for Partially Shaded PV System Using Hybrid DEPSO Method , 2015, IEEE Transactions on Sustainable Energy.

[4]  Chung-Yuen Won,et al.  A new maximum power point tracker of photovoltaic arrays using fuzzy controller , 1994, Proceedings of 1994 Power Electronics Specialist Conference - PESC'94.

[5]  Haihua Hu,et al.  An NNwC MPPT-Based Energy Supply Solution for Sensor Nodes in Buildings and Its Feasibility Study , 2018 .

[6]  Mansour Souissi,et al.  Modeling and control of photovoltaic and fuel cell based alternative power systems , 2018, International Journal of Hydrogen Energy.

[7]  Saad Mekhilef,et al.  State of the art artificial intelligence-based MPPT techniques for mitigating partial shading effects on PV systems – A review , 2016 .

[8]  C. Larbes,et al.  Comparative study and performance evaluation of central and distributed topologies of photovoltaic system , 2017 .

[9]  Marcelo Godoy Simões,et al.  Fuzzy optimisation based control of a solar array system , 1999 .

[10]  Maysam F. Abbod,et al.  A novel maximum power point tracking technique based on fuzzy logic for photovoltaic systems , 2018, International Journal of Hydrogen Energy.

[11]  Susovon Samanta,et al.  Modified Perturb and Observe MPPT Algorithm for Drift Avoidance in Photovoltaic Systems , 2015, IEEE Transactions on Industrial Electronics.

[12]  M.B.R. Correa,et al.  Using the model of the solar cell for determining the maximum power point of photovoltaic systems , 2007, 2007 European Conference on Power Electronics and Applications.

[13]  Hossam Faris,et al.  Grasshopper optimization algorithm for multi-objective optimization problems , 2017, Applied Intelligence.

[14]  Hossam Faris,et al.  Evolutionary Population Dynamics and Grasshopper Optimization approaches for feature selection problems , 2017, Knowl. Based Syst..

[15]  Essam E. M. Mohamed,et al.  Modified efficient perturb and observe maximum power point tracking technique for grid-tied PV system , 2018, International Journal of Electrical Power & Energy Systems.

[16]  Chokri Ben Salah,et al.  Comparison of fuzzy logic and neural network in maximum power point tracker for PV systems , 2011 .

[17]  C. Larbes,et al.  Genetic algorithms optimized fuzzy logic control for the maximum power point tracking in photovoltaic system , 2009 .

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

[19]  M.A.S. Masoum,et al.  A new fuzzy-based maximum power point tracker for photovoltaic applications , 2005 .

[20]  Necmi Altin,et al.  Fuzzy logic based MPPT controller for high conversion ratio quadratic boost converter , 2017 .

[21]  Tey Kok Soon,et al.  A Fast-Converging MPPT Technique for Photovoltaic System Under Fast-Varying Solar Irradiation and Load Resistance , 2015, IEEE Transactions on Industrial Informatics.

[22]  Adel Mellit,et al.  A novel hybrid boost converter with extended duty cycles range for tracking the maximum power point in photovoltaic system applications , 2018 .

[23]  Kok Soon Tey,et al.  Modified Incremental Conductance Algorithm for Photovoltaic System Under Partial Shading Conditions and Load Variation , 2014, IEEE Transactions on Industrial Electronics.

[24]  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.

[25]  S. Kahla,et al.  Fuzzy-PSO controller design for maximum power point tracking in photovoltaic system , 2017 .

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

[27]  Abdelhamid Rabhi,et al.  Optimization of Scaling Factors of Fuzzy–MPPT Controller for Stand-alone Photovoltaic System by Particle Swarm Optimization , 2017 .

[28]  Saad Mekhilef,et al.  A review on solar energy use in industries , 2011 .

[29]  N. V. Srikanth,et al.  Load frequency control for diverse sources of interconnected two area power system: An adaptive fuzzy approach , 2016, 2016 International Conference on Control, Computing, Communication and Materials (ICCCCM).

[30]  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.

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

[32]  A. Kunakorn,et al.  A novel fuzzy logic control technique tuned by particle swarm optimization for maximum power point tracking for a photovoltaic system using a current-mode boost converter with bifurcation control , 2010 .

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

[34]  Jawad Ahmad,et al.  A fractional open circuit voltage based maximum power point tracker for photovoltaic arrays , 2010, 2010 2nd International Conference on Software Technology and Engineering.

[35]  L.A.C. Lopes,et al.  An improved perturbation and observation maximum power point tracking algorithm for PV arrays , 2004, 2004 IEEE 35th Annual Power Electronics Specialists Conference (IEEE Cat. No.04CH37551).

[36]  Ekaitz Zulueta,et al.  Novel control algorithm for MPPT with Boost converters in photovoltaic systems , 2017 .

[37]  Hassan Fathabadi,et al.  Novel fast dynamic MPPT (maximum power point tracking) technique with the capability of very high accurate power tracking , 2016 .

[38]  Attia A. El-Fergany,et al.  Electrical characterisation of proton exchange membrane fuel cells stack using grasshopper optimiser , 2018 .

[39]  S. Sheik Mohammed,et al.  A novel hybrid Maximum Power Point Tracking Technique using Perturb & Observe algorithm and Learning Automata for solar PV system , 2016 .

[40]  Anil Annamraju,et al.  Fuzzy Logic Approach Based Novel Frequency Control Strategy by Wind Turbine Generator in a Wind-Diesel Autonomous Microgrid , 2019, 2019 IEEE 1st International Conference on Energy, Systems and Information Processing (ICESIP).

[41]  Luigi Piegari,et al.  Adaptive perturb and observe algorithm for photovoltaic maximum power point tracking , 2010 .

[42]  Moulay Fatima,et al.  A detailed modeling of photovoltaic module using MATLAB , 2014 .

[43]  M. Adly,et al.  An optimized fuzzy maximum power point tracker for stand alone photovoltaic systems: Ant colony approach , 2012, 2012 7th IEEE Conference on Industrial Electronics and Applications (ICIEA).

[44]  S. S. Darly,et al.  Application of QOCGWO-RFA for maximum power point tracking (MPPT) and power flow management of solar PV generation system , 2020 .