Micheal Abimbola Oladosu¹*, Moses Adondua Abah², Jesse Chigozirim Nwankwo3, Olaoluwa John Adeleke⁴, Joshua Kehinde Omopariola⁵, Oluwafemi Jeremiah Oluwasanmi⁶, Jeremiah Oluwayomi Oladetan⁷, Ekele Angel Ojimaojo⁸ and Olaide Ayokunmi Oladosu⁹
¹Department of Chemical Sciences, Faculty of Science, Anchor University, Ayobo, Lagos, Nigeria
²Department of Biochemistry, Faculty of Pure and Applied Sciences, Federal University of Wukari, Wukari, Taraba State, Nigeria
3Department of Chemistry, Faculty of Arts and Sciences, Prairie View A&M University, Prairie View, Texas, USA
⁴Department: Electrical Engineering, School of Engineering, The Polytechnic Ibadan, Ibadan, Oyo, Nigeria
5Department of Mechanical Engineering, Faculty of Engineering, Federal University Oye Ekiti, Ekiti State, Nigeria
⁶Department of Mechanical Engineering, School of Engineering and Engineering Technology, Federal University of Technology, Akure, Ondo State, Nigeria
⁷Department of Aerospace Engineering, Faculty of Engineering, Lagos State University, Iyana-Ibaja, Lagos, Nigeria
⁸Department of Biochemistry, Faculty of Pure and Applied Sciences, Federal University of Wukari, Wukari, Taraba State, Nigeria
⁹Department of Computer Science, Faculty of Science and Technology, Babcock University, Ilishan, Nigeria
(✉) Corresponding Author
Received: May 2, 2026/ Revised: June 2 2026/Accepted: June 12, 2026
Highlights
- Systematically reviews CFD applications across major renewable energy technologies.
- Demonstrates CFD-driven improvements in efficiency, heat transfer, and power generation.
- Examines performance optimisation in wind, solar thermal, hydrokinetic, and geothermal systems.
- Highlights CFD as a powerful tool for design optimisation and flow-field analysis.
- Identifies future opportunities in multiphysics modelling, machine learning, and real-time optimisation
Abstract
Computational Fluid Dynamics (CFD) is now a tool that cannot be ignored in the optimisation of the performance of a renewable energy system by making it easier to explain the fluid dynamical phenomena that literally affect the performance and energy conversion efficiency. The current systematic review provides a broad synthesis of the existing body of knowledge about the application of CFD in a wide variety of renewable energy technologies. The literature review was conducted through a wide range of databases: Web of Science, Scopus, and IEEE Xplore, and included the literature that was published between 2015 and 2024. Keywords included: computational fluid dynamics, CFD, renewable energy, wind turbine, solar thermal, hydrokinetic and performance optimisation. The studies that had used CFD simulations to analyse renewable energy systems and reported an objective performance measure were eligible. A total of 247 studies were obtained in the search, of which 156 met the inclusion criteria. The largest portion (45 per cent) was made up of wind energy applications, then there were solar thermal systems (28%), hydrokinetic systems (18%) and geothermal applications (9%). Significant performance improvements were gained with the use of CFD, with efficiency improvements of 8-25% in wind turbines, 12-35% in heat transfer in solar collectors, and power- output improvements of 15-30% in hydrokinetic machines. It has been shown that CFD plays a significant role in the improvement of the performance of the renewable energy systems, especially in terms of providing detailed flow analysis, optimisation of the design and determining the working parameters. Further research must be directed at the aspects of multi- physics coupling, integration of machine-learning techniques, and the creation of real-time optimisation solutions.
Keywords: computational fluid dynamics, renewable energy, performance optimisation, wind energy, solar thermal, hydrokinetic energy
How to cite this article
Oladosu, M. A., Abah, M. A., Nwankwo, J. C., Adeleke, O. J., Omopariola, J. K., Oluwasanmi, O. J., Olayomi, J. O., Ojimaojo, E. A., & Oladosu, O. A. (2026). Computational fluid dynamics for performance optimisation in renewable energy systems: A systematic review. Science Archives, 7(2), 270–283. https://doi.org/10.47587/SA.2026.7224
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