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Evaluation of On-Line MPPT Algorithms for PV-Based Battery Storage Systems

Belqasem Aljafari1, Eydhah Almatrafi2,3,4, Sudhakar Babu Thanikanti5, Sara A. Ibrahim6, Mohamed A. Enany6,*, Marwa M. Ahmed7

1 Electrical Engineering Department, College of Engineering, Najran University, Najran, 11001, Saudi Arabia
2 Mechanical Engineering Department, College of Engineering-Rabigh, King Abdulaziz University, Jeddah, Saudi Arabia
3 K. A. CARE Energy Research and Innovation Center, King Abdulaziz University, Jeddah, 21589, Saudi Arabia
4 Center of Excellence in Desalination Technology, King Abdulaziz University, Jeddah, Saudi Arabia
5 Department of Electrical and Electronics Engineering, Chaitanya Bharathi Institute of Technology, Hyderabad, 500075, India
6 Electrical Power and Machines Department, Faculty of Engineering, Zagazig University, Zagazig, 44519, Egypt
7 Electrical Engineering Department, Faculty of Engineering, King Abdul-Aziz University, Jeddah, 80204, Saudi Arabia

* Corresponding Author: Mohamed A. Enany. Email: email

Computers, Materials & Continua 2022, 73(2), 3595-3611.


This paper presents a novel Simulink models with an evaluation study of more widely used On-Line Maximum Power Point tracking (MPPT) techniques for Photo-Voltaic based Battery Storage Systems (PV-BSS). To have a full comparative study in terms of the dynamic response, battery state of charge (SOC), and oscillations around the Maximum Power Point (MPP) of the PV-BSS to variations in climate conditions, these techniques are simulated in Matlab/Simulink. The introduced methodologies are classified into two types; the first type is conventional hill-climbing techniques which are based on instantaneous PV data measurements such as Perturb & Observe and Incremental Conductance techniques. The second type is a novel proposed methodology is based on using solar irradiance and cell temperature measurements with pre- build Adaptive Neuro-Fuzzy Inference System (ANFIS) model to predict DC–DC converter optimum duty cycle to track MPP. Then evaluation study is introduced for conventional and proposed On-Line MPPT techniques. This comparative study can be useful in specifying the appropriateness of the MPPT techniques for PV-BSS. Also the introduced model can be used as a valued reference model for future research related to Soft Computing (SC) MPPT techniques. A significant improvement of SOC is achieved by the proposed model and methodology with high accuracy and lower oscillations.


Cite This Article

B. Aljafari, E. Almatrafi, S. Babu Thanikanti, S. A. Ibrahim, M. A. Enany et al., "Evaluation of on-line mppt algorithms for pv-based battery storage systems," Computers, Materials & Continua, vol. 73, no.2, pp. 3595–3611, 2022.

cc This work is licensed under a Creative Commons Attribution 4.0 International License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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