Wind Flow Characterisation over a PV Module through URANS Simulations and Wind Tunnel Optical Flow Methods
Francesco Castellani,
Abdelgalil Eltayesh,
Francesco Natili,
Tommaso Tocci,
Matteo Becchetti,
Lorenzo Capponi,
Davide Astolfi and
Gianluca Rossi
Additional contact information
Francesco Castellani: Department of Engineering, University of Perugia, Via G. Duranti 93, 06125 Perugia, Italy
Abdelgalil Eltayesh: Mechanical Engineering Department, Benha Faculty of Engineering, Benha University, Benha 13512, Egypt
Francesco Natili: Department of Engineering, University of Perugia, Via G. Duranti 93, 06125 Perugia, Italy
Tommaso Tocci: Department of Engineering, University of Perugia, Via G. Duranti 93, 06125 Perugia, Italy
Matteo Becchetti: Department of Engineering, University of Perugia, Via G. Duranti 93, 06125 Perugia, Italy
Lorenzo Capponi: Department of Engineering, University of Perugia, Via G. Duranti 93, 06125 Perugia, Italy
Davide Astolfi: Department of Engineering, University of Perugia, Via G. Duranti 93, 06125 Perugia, Italy
Gianluca Rossi: Department of Engineering, University of Perugia, Via G. Duranti 93, 06125 Perugia, Italy
Energies, 2021, vol. 14, issue 20, 1-21
Abstract:
Despite their simplicity, photovoltaic (PV) modules are often arranged in structures that can be affected by severe and complex wind loads: in this context, the wind flow and the dynamic excitation induced by vortex shedding can introduce unexpected aeroelastic responses. This work introduces a novel wind tunnel application of experimental techniques to address this issue by the use of flow visualisation and video postprocessing, through the optical flow algorithm. Numerical simulations based on unsteady Reynolds-averaged Navier–Stokes (RANS) models are performed and compared against the experimental wind tunnel tests on a PV panel that was also instrumented with pressure taps. A setup with a 65 ∘ tilt angle was examined because, based on preliminary analyses, it was considered interesting for the free flow–wake transition associated with the dynamic response of the PV panel. The comparison of the experimental and numerical average wind fields supported that the proposed optical flow method was appropriate for characterising the wake of the panel, because there was enough seeding to perform the video postprocessing. Experiments and numerical predictions were compared as regards the average pressure distribution on the panel surfaces, and the average percentage was in the error of 7%; this supports that the URANS method was capable of reproducing the average behaviour of the panel, as well as for the selected configuration, which is particularly challenging. Furthermore, the simulated and measured power spectral densities of the wind speed were compared, and this resulted in the numerical model quite faithfully reproducing the frequency of the peak at 5 m/s, while the error was in the order of 20% for the 10 m/s case; this supports that, despite the URANS approach being affected by well-known critical points regarding the simulation of instantaneous quantities, it can be employed to elaborate information that can be particularly useful for the structural design of the panel. This kind of result can be considered as a first step, obtained with simplified and affordable methods, towards a characterisation of the dynamic behaviour of a PV panel in a real-world setup.
Keywords: photovoltaic; aeroelasticity; wind tunnel test; optical flow; computational fluid dynamics; sustainable energy (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2021
References: View references in EconPapers View complete reference list from CitEc
Citations:
Downloads: (external link)
https://www.mdpi.com/1996-1073/14/20/6546/pdf (application/pdf)
https://www.mdpi.com/1996-1073/14/20/6546/ (text/html)
Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
HTML/Text
Persistent link: https://EconPapers.repec.org/RePEc:gam:jeners:v:14:y:2021:i:20:p:6546-:d:654172
Access Statistics for this article
Energies is currently edited by Ms. Agatha Cao
More articles in Energies from MDPI
Bibliographic data for series maintained by MDPI Indexing Manager ().