journal article·2024-08-29Open access

Comparative Study of a Buck DC-DC Converter Controlled by the MPPT (P&O) Algorithm without or with Fuzzy Logic Controller

Petru Livinti, George Culea, Ioan Viorel Banu, Sorin Gabriel Vernica

Applied Sciences· Volume 14· Issue 17

Abstract

This work presents a comparative study of a step-down converter controlled through the algorithm MPPT Perturb and Observe (P&O) with or without a fuzzy logic controller supplied by a photovoltaic system. This study aimed at increasing the quantity of electric energy taken over from the photovoltaic systems by the load through the DC-DC convertor. To follow up the maximum power point where the transfer is performed from the photovoltaic system to the load at maximum power, the Perturb and Observe (P&O) method was used. Two programs were elaborated in MATLAB-Simulink R2018a to control the buck convertor commanded through the P&O algorithm with or without a fuzzy logic controller. The analysis of the results showed that a higher quantity of energy is transferred from the source to the receptor circuit in the case of the buck convertor controlled through the P&O algorithm with a fuzzy logic controller. The P&O algorithm was implemented on an experimental stand at the Laboratory of Electrical Machinery and Drives of the Engineering Faculty in Bacau, with the help of a program issued in the Arduino IDE programming environment. The analysis of the results showed that for an increase in the power conveyed to the receptor circuit, there will also be an increase in the filling factor of the PWM signal that controls the power transistor in the structure of the DC-DC convertor. The P&O algorithm with a fuzzy logic controller may also be implemented in the DC-DC converters in the structure of the driving systems of electric vehicles.
Source: crossref · Quality: baseline

Research context

OpenAlex topics: Photovoltaic System Optimization Techniques · Advanced Battery Technologies Research · Solar Radiation and Photovoltaics

SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.

Affiliations

The Department of Power Engineering and Computer Science, Faculty of Engineering, University “Vasile Alecsandri” of Bacau, 600115 Bacau, Romania

Funding

University “Vasile Alecsandri” of Bacau from the funds allocated for research

References (26)

Show source-provided references
1. Comparative Study of MPPT Controllers for PV System Implemented in the South-west of Algeria10.1016/j.egypro.2013.07.017 ↗
2. Boubii, C., El Kafazi, I., Bannari, R., and El Bhiri, B. (2023, January 29). A comparative study between optimization algorithms of MPPT algorithms (P&O and incremental conductance method). Proceedings of the International Conference on Digital Technologies and Applications 2023, Fez, Morocco.10.1007/978-3-031-29857-8_61 ↗
3. Comparative Study of Different DC/DC Power Converter for Optimal PV System Using MPPT (P&O) Method10.3103/S0003701X18040047 ↗
4. Meryem, B., Ahmed, N., and Ahmed, F. (2024, July 17). Photovoltaic Power Control Using Fuzzy Logic and Fuzzy Logic Type 2 MPPT Algorithms and Buck Converter. Available online: https://core.ac.uk/download/pdf/228834734.pdf.
5. Balta, G., Altin, N., and Nasiri, A. (2023). Interval Type-2 Fuzzy-Logic-Based Constant Switching Frequency Control of a Sliding-Mode-Controlled DC–DC Boost Converter. Appl. Sci., 13.10.3390/app13053239 ↗
6. Agoub, R.A.A., Hançerlioğullari, A., Rahebi, J., and Lopez-Guede, J.M. (2023). Battery Charge Control in Solar Photovoltaic Systems Based on Fuzzy Logic and Jellyfish Optimization Algorithm. Appl. Sci., 13.10.3390/app132011409 ↗
7. Baždarić, R., Ćelić, J., and Vončina, D. (2023). Compensation of the Current Imbalance of an Interleaved DC–DC Buck Converter, Sensorless Online Solution Based on Offline Fuzzy Identification and Post-Linearization. Energies, 16.10.3390/en16124836 ↗
8. Design and Operation of Fuzzy Logic Based MPPT Controller under Uncertain Condition10.1088/1742-6596/1854/1/012035 ↗
9. Tatar, K., Chudzik, P., and Leśniewski, P. (2023). Sliding Mode Control of Buck DC–DC Converter with LC Input Filter. Energies, 16.10.3390/en16196983 ↗
10. Monsalve-Rueda, M., Candelo-Becerra, J.E., and Hoyos, F.E. (2024). A Comparative Study between MPC Algorithm and P&O and IncCond the Optimization Algorithms of MPPT Algorithms. Energies, 17.10.3390/en17112701 ↗
11. Li, X., He, Y., and Li, M. (2024). Research on Photovoltaic Maximum Power Point Tracking Control Based on Improved Tuna Swarm Algorithm and Adaptive Perturbation Observation Method. Energies, 17.10.3390/en17122985 ↗
12. Cai, Z., Tang, Y., Guo, W., Chen, T., Zheng, H., and Qin, T. (2024). Energy Management Strategy for Distributed Photovoltaic 5G Base Station DC Microgrid Integrated with the CF-P&O-INC MPPT Algorithm. Energies, 17.10.3390/en17133258 ↗
13. Almousa, M.T., Gomaa, M.R., Ghasemi, M., and Louzazni, M. (2024). Single-Sensor Global MPPT for PV System Interconnected with DC Link Using Recent Red-Tailed Hawk Algorithm. Energies, 17.10.3390/en17143391 ↗
14. Rezk, H., Aly, M., and Ghoniem, R.M. (2023). Robust Fuzzy Logic MPPT Using Gradient-Based Optimization for PEMFC Power System. Sustainability, 15.10.3390/su151813368 ↗
15. Khan, M.U., Murtaza, A.F., Noman, A.M., Sher, H.A., and Zafar, M. (2024). State-Space Modeling, Design, and Analysis of the dc-dc Converters for PV Application: A Review. Sustainability, 16.10.3390/su16010202 ↗
16. Subbulakshmy, R., Palanisamy, R., Alshahrani, S., and Saleel, C.A. (2024). Implementation of Non-Isolated High Gain Interleaved DC-DC Converter for Fuel Cell Electric Vehicle Using ANN-Based MPPT Controller. Sustainability, 16.10.3390/su16031335 ↗
17. El Abbadi, R., Aatabe, M., and Bouzid, A.E.M. (2024). Wireless Diagnosis and Control of DC–DC Converter for Off-Grid Photovoltaic Systems. Sustainability, 16.10.3390/su16083252 ↗
18. Yilmaz, M. (2024). Comparative Analysis of Hybrid Maximum Power Point Tracking Algorithms Using Voltage Scanning and Perturb and Observe Methods for Photovoltaic Systems under Partial Shading Conditions. Sustainability, 16.10.3390/su16104199 ↗
19. Banu, I.V., Beniugă, R., and Istrate, M. (2013, January 23–25). Comparative Analysis of the Perturb-and-Observe and Incremental Conductance MPPT Methods. Proceedings of the 8th International Symposium on Advanced Topics in Electrical Engineering, Bucharest, Romania.10.1109/ATEE.2013.6563483 ↗
20. Comparison of Photovoltaic Array Maximum Power Point Tracking Techniques10.1109/TEC.2006.874230 ↗
21. Comparison of MPPT Algorithms for DC-DC Converters Based PV Systems
22. MPPT techniques for photovoltaic systems: A systematic review in current trends and recent advances in artificial intelligence10.1007/s43937-023-00024-2 ↗
23. Rekioua, D., and Matagne, E. (2012). Optimization of Photovoltaic Power Systems, Modelization, Simulation and Control, Springer.10.1007/978-1-4471-2403-0 ↗
24. Sofron, E., Bizon, N., Ionita, S., and Raducu, R. (2021, February 26). Sisteme de Control Fuzzy—Modelare si Proiectare Asistate de Calculator. Available online: https://igsbiera.ebibliophil.ro/mon/sisteme-de-control-fuzzy-modelare-si-proiectare-asistate-de-calculator-tehnologii-avansate-h29yrjz4.
25. (2024, July 17). Available online: https://www.wardsci.com/store/product/23748699/arduino-uno-development-board.
26. Study of arduino microcontroller board