# Experimental Assessment of RANS Models for Wind Load Estimation over Solar-Panel Arrays
## 1 Introduction  
Solar panels are generally designed to withstand a frontal wind with predetermined intensity [1]; load reduction due to the arrangement of the elements of a solar-panel array is not considered in the design phase. In a solar-panel array, the first panel row deflects the incoming wind, producing a separated and turbulent wake that impacts against the following panels. Due to shielding effect, the other rows may benefit of smaller (on average) structural loads, but are also likely to be subjected to unsteady forces generated in the wake. More robust predictions of wind loads on solar panels would allow a reduction of the maintenance costs and of the manufacturing price of the support structure. This costs reduction will improve the competitive capacity of this type of energy. [PERSON] et al. [2] have shown that, due to capital costs, the current market price of solar power is still higher than what could be achieved by conventional systems (e.g., nuclear, coal, gas). Nevertheless solar energy might become competitive in the short future. [PERSON] et al. [3] identified a possible strategy to cut the capital cost of solar arrays in the simplification of the panels design and thus in their structural optimization. Additionally, wind loads might add on top of other climate parameter (such as temperature, humidity, etc., see e.g., [4]) affecting the aging and performance degradation of photo-voltaic panels [5, 6, 7]. In this frame, a proper characterisation of the wind loads on panel arrays must be performed,also considering that these loads are far from being negligible. In the recent years, in fact, solar panels have become a quite popular solution in small communities to achieve energy independence or, in extended power grids, to provide a distributed energy resource nearby load centers, therefore cutting the energy transmission and distribution costs. In these applications, panels are typically mounted on building rooftops, where they have to face sustained winds. The flow field and loads affecting rooftop-mounted solar panels have been analyzed by several studies in the literature [8; 9; 10; 11]. Both numerical [12; 13; 14; 15; 16] and experimental [17; 18; 19; 20] studies have been carried out in order to analyse the wind loads on solar panels in both single- and multiple-array configuration. [PERSON] et al. [12] performed simulations both on a single panel and on a three-panels array. The simulations consisted of an initial run using Reynolds-Averaged Navier-Stokes (RANS) simulation, aimed at obtaining reliable initial conditions, followed by a run using Large-Eddy Simulation (LES). Their results showed that the magnitude of the pressure coefficients was generally underestimated by the numerical calculations when compared to the experimental results, although the same patterns of pressure coefficient distribution was found. The study also provides evidence of the shielding effect. [PERSON] and [PERSON] [13] performed several RANS simulations with \(k\)-\(\epsilon\), \(k\)-\(\omega\) and Reynolds-Stress Model (RSM) turbulence closure models. The study analyzed the flow field around a single solar panel for different wind direction and different panel inclinations. Their results showed that the critical cases for the loads on the solar panel correspond with the wind direction \(0^{\circ}\) and \(180^{\circ}\). [PERSON] et al. [14] also performed RANS simulations with Shear-Stress Transport (SST) \(k\)-\(\omega\) and \(k\)-\(\epsilon\) closure models discretising the solar panel into a 2 \(\times\) 2 sub-panels and varying the gap between them. Their results showed that bottom panels experience larger mean wind loading compared to the top panels. Although the introduction of gap spacing results in reduced mean wind forces, it produces regions that experience larger wind loading. Moreover, the increase of the ground clearance also causes larger mean wind loading on the panels. [PERSON] and [PERSON] [15] performed a RANS simulation with SST \(k\)-\(\omega\) closure models.