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

2021 ◽  
Vol 11 (16) ◽  
pp. 7732
Author(s):  
Habib Kraiem ◽  
Flah Aymen ◽  
Lobna Yahya ◽  
Alicia Triviño ◽  
Mosleh Alharthi ◽  
...  
Keyword(s):  
Electric Vehicle ◽  
Control Strategies ◽  
Storage System ◽  
Particle Swarm ◽  
Optimization Method ◽  
Photovoltaic System ◽  
Grey Wolf ◽  
Grey Wolf Optimization ◽  
Partial Shading ◽  
Point Tracking

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.

scholarly journals The efficiency of PSO-based MPPT technique of an electric vehicle within the city

2020 ◽  
Vol 53 (3-4) ◽  
pp. 461-473
Author(s):  
Habib Kariem ◽  
Ezzedine Touti ◽  
Tamer Fetouh
Keyword(s):  
Particle Swarm Optimization ◽  
Electric Vehicle ◽  
Performance Indicators ◽  
Particle Swarm ◽  
Optimization Method ◽  
Energy Performance ◽  
Photovoltaic System ◽  
Swarm Optimization ◽  
Particle Swarm Optimization Method ◽  
The City

Electrical vehicle fed by photovoltaic energy represents a complex system, which needs a high-performance control algorithm. Regarding the real situations, mostly the electric vehicle will be moving inside the city. If this system is covered by photovoltaic cells, the efficiency of this renewable energy source will depend on various factors. The shade areas or sunlight zones which exist in the city make the solar system unstable. Resolving this problem can increase the battery autonomy and allow addition of some running kilometers to the vehicle. Based on this objective, this study deals with the problem of solar variation and its influence on vehicle efficiency within the city. The problem is how to extract the maximum energy in this case. In order to maximize the global energy performance and increase vehicle autonomy, the optimal control method will be applied to this photovoltaic system taking into account some performance indicators such as the obtained power, the tracking speed, and the chattering level. Therefore, this study explores two control techniques in order to extract the maximum power from the solar energy system, which are the incremental method and the particle swarm optimization method. Simulink/MATLAB tool is used for simulation and comparison study based on the offered performance indicators. The obtained results show that the particle swarm optimization method has high global performance and an energy gain is obtained.

MPPT-based on Bat algorithm for photovoltaic systems working under partial shading conditions

2021 ◽  
pp. 1-9
Author(s):  
Mohammed Asim ◽  
Piyush Agrawal ◽  
Mohd Tariq ◽  
Basem Alamri
Keyword(s):  
Low Cost ◽  
Bat Algorithm ◽  
Photovoltaic System ◽  
Maximum Power Point ◽  
Partial Shading ◽  
Point Tracking ◽  
Power Point Tracking ◽  
Full Power ◽  
Power Point ◽  
Global Peak

Under partial shading conditions (PSC), most traditional maximum power point tracking (MPPT) techniques may not adopt GP (global peak). These strategies also often take a considerable amount of time to reach a full power point (MPP). Such obstacles can be eliminated by the use of metaheuristic strategies. This paper shows, in partial shading conditions, the MPPT technique for the photovoltaic system using the Bat Algorithm (BA). Simulations have been performed in the MATLAB ®/Simulink setting to verify the efficacy of the proposed method. In MPPT applications, the results of the simulations emphasize the precision of the proposed technique. The algorithm is also simple and efficient, on a low-cost microcontroller, it could be implemented. Hardwar in loop (HIL) validation is performed, with a Typhoon HIL 402 setup.

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