EN
An Adaptive Hybrid Algorithm for MPPT in Battery-Backed Solar and Wind Energy Systems
Abstract
Renewable energy systems, including solar, wind and hydro, have gained significant importance in recent years. Although these systems have many advantages, such as being clean and sustainable, their key disadvantage is low efficiency comparing to the energy systems based on fossil fuels. Moreover, more land area and resources are required by renewable energy sources to produce equal amount of energy compared to conventional sources. The efficiency of renewable energy systems can be improved using some selected techniques, which extract maximum power under all possible conditions. In this paper, a comparative analysis of eight different algorithms, including simple and artificial maximum power tracking techniques, has been conducted for wind and solar energy systems with integrated load and storage components. The comparison was based on factors such as efficiency, settling time, oscillations at maximum power point, and complexity of the algorithm. By combining the benefits of artificial intelligence and conventional methods, an adaptive hybrid algorithm that produced superior results is proposed for renewable energy systems.
Keywords
References
- [1] Tourqui, D.E., Betka, A., Smaili, A., Allaoui, T. “Design and implementation of a digital MPPT controller for a photovoltaic panel”, Turkish Journal of Electrical Engineering and Computer Sciences, 24(6): 5135-5149, (2016). https://doi.org/10.3906/elk-1503-41
- [2] Boutabba, T., Drid, S., Chrifi-Alaoui, L., Mehdi, D., Benbouzid., “Real-time implementation of sliding mode maximum power point tracker for photovoltaic system”, 7th International Conference on Systems and Control, ICSC 2018, València (2018).
- [3] Tarek, B., Drid, S., Benbouzid, M., “A multi-output boost converter (MOB) controlled by fuzzy logic technique supplied by a photovoltaic system with grid-connected and fed by three level inverters”, International Conference on Electro-Energy, ICEE’14, 10–11, (2014).
- [4] Vijayalakshmi R., Nazar Ali A., “Hybrid power generations (wind/solar by PV)—an efficient output with reduced total harmonics distortions using multi-level inverter”, International Conference on Electro-Energy, (2012).
- [5] Rana, M., Ali, R., Ajad, A.K., “Analysis of P&O and INC MPPT Techniques for PV Array Using MATLAB”, Journal of Electrical and Electronics Engineering (IOSR-JEEE), 11(4): 80-86, (2016). DOI: 10.9790/1676-1104028086
- [6] Chaudhary, S., Singh, A., “Analysis of AI Techniques for Maximum Power Point Tracking Under Partial Shading Conditions”, IEEE 17th India Council International Conference (INDICON), 1-6, (2020). 10.1109/INDICON49873.2020.9342154
- [7] Mahdi, A.S., Mahamad A.K., Saon S., Tuwoso, T., Elmunsyah, H., Mudjanarko, S.W., et al., “Maximum power point tracking using perturb and observe, fuzzy logic and ANFIS”, SN Appl. Sci. 2: 89-95, (2020). https://doi.org/10.1007/s42452-019-1886-1
- [8] Abd El-Shafy A. Nafeh, “Optimal economical sizing of a PV-wind hybrid energy system using genetic algorithm”, International Journal of Green Energy, 8(1): 25-43, (2011). https://doi.org/10.1080/15435075.2010.529407
Details
Primary Language
English
Subjects
Electrical Energy Generation (Incl. Renewables, Excl. Photovoltaics)
Journal Section
Research Article
Early Pub Date
January 30, 2026
Publication Date
January 30, 2026
Submission Date
May 27, 2025
Acceptance Date
January 28, 2026
Published in Issue
Year 2026 Volume: 39 Number: 2
APA
Ahmad, M. S., & Sünter, S. (2026). An Adaptive Hybrid Algorithm for MPPT in Battery-Backed Solar and Wind Energy Systems. Gazi University Journal of Science, 39(2), 619-635. https://doi.org/10.35378/gujs.1707158
AMA
1.Ahmad MS, Sünter S. An Adaptive Hybrid Algorithm for MPPT in Battery-Backed Solar and Wind Energy Systems. Gazi University Journal of Science. 2026;39(2):619-635. doi:10.35378/gujs.1707158
Chicago
Ahmad, Muhammad Saeed, and Sedat Sünter. 2026. “An Adaptive Hybrid Algorithm for MPPT in Battery-Backed Solar and Wind Energy Systems”. Gazi University Journal of Science 39 (2): 619-35. https://doi.org/10.35378/gujs.1707158.
EndNote
Ahmad MS, Sünter S (June 1, 2026) An Adaptive Hybrid Algorithm for MPPT in Battery-Backed Solar and Wind Energy Systems. Gazi University Journal of Science 39 2 619–635.
IEEE
[1]M. S. Ahmad and S. Sünter, “An Adaptive Hybrid Algorithm for MPPT in Battery-Backed Solar and Wind Energy Systems”, Gazi University Journal of Science, vol. 39, no. 2, pp. 619–635, June 2026, doi: 10.35378/gujs.1707158.
ISNAD
Ahmad, Muhammad Saeed - Sünter, Sedat. “An Adaptive Hybrid Algorithm for MPPT in Battery-Backed Solar and Wind Energy Systems”. Gazi University Journal of Science 39/2 (June 1, 2026): 619-635. https://doi.org/10.35378/gujs.1707158.
JAMA
1.Ahmad MS, Sünter S. An Adaptive Hybrid Algorithm for MPPT in Battery-Backed Solar and Wind Energy Systems. Gazi University Journal of Science. 2026;39:619–635.
MLA
Ahmad, Muhammad Saeed, and Sedat Sünter. “An Adaptive Hybrid Algorithm for MPPT in Battery-Backed Solar and Wind Energy Systems”. Gazi University Journal of Science, vol. 39, no. 2, June 2026, pp. 619-35, doi:10.35378/gujs.1707158.
Vancouver
1.Muhammad Saeed Ahmad, Sedat Sünter. An Adaptive Hybrid Algorithm for MPPT in Battery-Backed Solar and Wind Energy Systems. Gazi University Journal of Science. 2026 Jun. 1;39(2):619-35. doi:10.35378/gujs.1707158