A Comparison between Particle Swarm and Grey Wolf Optimization Algorithms for Improving the Battery Autonomy in a Photovoltaic System

This research focuses on a photovoltaic system that powers an Electric Vehicle when moving in realistic scenarios with partial shading conditions. The main goal is to find an efficient control scheme to allow the solar generator producing the maximum amount of power achievable. The first contribution of this paper is the mathematical modelling of the photovoltaic system, its function and its features, considering the synthesis of the step-up converter and the maximum power point tracking analysis. This research looks at two intelligent control strategies to get the most power out, even with shading areas. Specifically, we show how to apply two evolutionary algorithms for this control. They are the “particle swarm optimization method” and the “grey wolf optimization method”. These algorithms were tested and evaluated when a battery storage system in an Electric Vehicle is fed through a photovoltaic system. The Simulink/Matlab tool is used to execute the simulation phases and to quantify the performances of each of these control systems. Based on our simulation tests, the best method is identified.

[1]  Kamal Bansal,et al.  Fire Hazards and Overheating Caused by Shading Faults on Photo Voltaic Solar Panel , 2016 .

[2]  Hong-ping Zhu,et al.  Vibration-Based Structural Damage Identification under Varying Temperature Effects , 2018 .

[3]  Carlos Robles-Algarín,et al.  Code and data from an ADALINE network trained with the RTRL and LMS algorithms for an MPPT controller in a photovoltaic system , 2020, Data in brief.

[4]  Sadiq M. Sait,et al.  Comparison of metaheuristic optimization algorithms for solving constrained mechanical design optimization problems , 2021, Expert Syst. Appl..

[5]  Masafumi Miyatake,et al.  Maximum Power Point Tracking of Multiple Photovoltaic Arrays: A PSO Approach , 2011, IEEE Transactions on Aerospace and Electronic Systems.

[6]  Ken Cai,et al.  Big Data Analysis Technology for Electric Vehicle Networks in Smart Cities , 2020, IEEE Transactions on Intelligent Transportation Systems.

[7]  Jingsen Liu,et al.  An Improved Gray Wolf Optimization Algorithm to Solve Engineering Problems , 2021, Sustainability.

[8]  Ahmed Bilal Awan,et al.  Swarm Intelligence-Based Optimization Techniques for Dynamic Response and Power Quality Enhancement of AC Microgrids: A Comprehensive Review , 2020, IEEE Access.

[9]  Majed Alowaidi,et al.  Increasing Electric Vehicle Autonomy Using a Photovoltaic System Controlled by Particle Swarm Optimization , 2021, IEEE Access.

[10]  S. Islam,et al.  A review: Energy storage system and balancing circuits for electric vehicle application , 2020, IET Power Electronics.

[11]  Mohammed Ali Khan,et al.  Fault diagnosis of Photovoltaic Modules , 2019, Energy Science & Engineering.

[12]  Seddik Bacha,et al.  Forecasting photovoltaic array power production subject to mismatch losses , 2010 .

[13]  Akbar Rahideh,et al.  Determination of the optimal location for constructing solar photovoltaic farms based on multi-criteria decision system and Dempster–Shafer theory , 2020, Scientific Reports.

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

[15]  Kuei-Hsiang Chao,et al.  A Hybrid MPPT Controller Based on the Genetic Algorithm and Ant Colony Optimization for Photovoltaic Systems under Partially Shaded Conditions , 2021, Energies.

[16]  Ziad M. Ali,et al.  Efficient Power Management Strategy of Electric Vehicles Based Hybrid Renewable Energy , 2021, Sustainability.

[17]  Yongzhi Lei,et al.  Structural Damage Identification Based on l1Regularization and Bare Bones Particle Swarm Optimization with Double Jump Strategy , 2019 .

[18]  Safwan Nadweh,et al.  Steady state analysis of modern industrial variable speed drive systems using controllers adjusted via grey wolf algorithm & particle swarm optimization , 2020, Heliyon.

[19]  Muhammad Hosnee Mobarak,et al.  Solar-Charged Electric Vehicles: A Comprehensive Analysis of Grid, Driver, and Environmental Benefits , 2021, IEEE Transactions on Transportation Electrification.

[20]  Carlos Robles Algarín,et al.  Data from a photovoltaic system using fuzzy logic and the P&O algorithm under sudden changes in solar irradiance and operating temperature , 2018, Data in brief.

[21]  Majed Alowaidi,et al.  Electric Vehicle Model Based on Multiple Recharge System and a Particular Traction Motor Conception , 2021, IEEE Access.

[22]  T. Fetouh,et al.  The efficiency of PSO-based MPPT technique of an electric vehicle within the city , 2020 .

[23]  Flah Aymen,et al.  BLDC Control Method Optimized by PSO Algorithm , 2019, 2019 International Symposium on Advanced Electrical and Communication Technologies (ISAECT).

[24]  Roberto Giral,et al.  Evaluation of particle swarm optimization techniques applied to maximum power point tracking in photovoltaic systems , 2021, Int. J. Circuit Theory Appl..

[25]  Yongzhi Lei,et al.  Structural damage identification based on modal frequency strain energy assurance criterion and flexibility using enhanced Moth-Flame optimization , 2020, Structures.

[26]  Ruzhu Wang,et al.  Concentrated solar energy applications using Fresnel lenses: A review , 2011 .

[27]  Akash Saxena,et al.  Parameter extraction of solar cell using intelligent grey wolf optimizer , 2020, Evol. Intell..

[28]  Bogdan Miedzinski,et al.  Photovoltaic systems , 2010, 2010 Modern Electric Power Systems.

[29]  Lucian Mihet-Popa,et al.  Evaluation of Mathematical Model to Characterize the Performance of Conventional and Hybrid PV Array Topologies under Static and Dynamic Shading Patterns , 2020 .

[30]  Ipek Cetinbas,et al.  Sizing optimization and design of an autonomous AC microgrid for commercial loads using Harris Hawks Optimization algorithm , 2021 .

[31]  Laiq Khan,et al.  Nonlinear adaptive NeuroFuzzy feedback linearization based MPPT control schemes for photovoltaic system in microgrid , 2020, PloS one.

[32]  Jung-Ik Ha,et al.  Design Principle and Loss Engineering for Photovoltaic–Electrolysis Cell System , 2017, ACS omega.

[33]  Habib Kraiem,et al.  Energy optimization of an electric car using losses minimization and intelligent predictive torque control , 2020 .

[34]  Andrew Lewis,et al.  Grey Wolf Optimizer , 2014, Adv. Eng. Softw..

[35]  Ching-Hsin Wang,et al.  Photovoltaic Modules Selection from Shading Effects on Different Materials , 2020, Symmetry.

[36]  Samia Nefti-Meziani,et al.  A Comprehensive Review of Swarm Optimization Algorithms , 2015, PloS one.