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The understanding of atmospheric flows is crucial in the analysis of dispersion of a contaminant or pollutant, wind energy and air-quality assessment to name a few. Additionally, the effects of complex terrain and associated orographic forcing are crucial in wind energy production. Furthermore, the use of the Reynolds-averaged Navier-Stokes (RANS) equations in the analysis of complex terrain is still considered the “workhorse” since millions of mesh points are required to accurately capture the details of the surface. On the other hand, solving the same problem by means of the instantaneous governing equations of the flow (i.e., in a suite of DNS or LES) would imply almost prohibitive computational resources. In this study, numerical predictions of atmospheric boundary layers are performed over a complex topography located in Nygårdsfjell, Norway. The Nygårdsfjell wind farm is located in a valley at approximately 420 meters above sea level surrounded by mountains in the north and south near the Swedish border. Majority of the winds are believed to be originated from Torneträsk lake in the east which is covered with ice during the winter time. The air closest to the surface on surrounding mountains gets colder and denser. The air then slides down the hill and accumulates over the lake. Later, the air spills out westward towards Ofotfjord through the broader channel that directs and transforms it into highly accelerated winds. Consequently, one of the objectives of the present article is to study the influence of local terrain on shaping these winds over the wind farm. It is worth mentioning that we are not considering any wind turbine model in the present investigation, being the main purpose to understand the influence of the local surface topography and roughness on the wind flow. Nevertheless, future research will include modeling the presence of a wind turbine and will be published elsewhere. The governing equations of the flow are solved by using a RANS approach and by considering three different two-equation turbulence models: k-omega (k–ω), k-epsilon (k–ε) and shear stress transport (SST). Furthermore, the real topographical characteristics of the terrain have been modeled by extracting the required area from the larger digital elevation model (DEM) spanning over 100 km square. The geometry is then extruded using Rhino and meshed in ANSYS Fluent. The terrain dimensions are approximately 2000×1000 meter square.

The objective of this study is to investigate the effect of temperature and wind speed on the performance of five photovoltaic (PV) module technologies for different climatic zones of Pakistan. The PV module technologies selected were mono-crystalline silicon (MC); poly-crystalline silicon (PC); heterogeneous intrinsic thin-film (TFH); copper–indium–allium–selenide (TFC); and thin-film amorphous silicon (TFA). The module temperature and actual efficiency were calculated using measured data for one year. The actual efficiency of MC, PC, TFH, TFC, and TFA decreases by 3.4, 3.1, 2.2, 3.7, and 2.7%, respectively, considering the effect of temperature only. The actual efficiency of MC, PC, TFH, TFC, and TFA increases by 9.7, 9.0, 6.5, 9.5, and 7.0% considering the effect of both temperature and wind speed. The TFH module is the most efficient (20.76%) and TFC is the least efficient (16.79%) among the five materials. Under the effect of temperature, the actual efficiency of TFH is the least affected while the efficiency of TFC is the most affected. The actual efficiency of MC is the most affected and that of TFH is the least affected under the combined effect of wind speed and temperature. The performance ratio of TFC is the most affected and that of TFH is the least affected under the effect of temperature and the combined effect of temperature and wind speed. The performance of PV technology, under real outdoor conditions, does not remain the same due to environmental stresses (solar irradiance, ambient temperature, and wind speed). This study plays an important role in quantifying the long-term behavior of PV modules in the field, hence identifying specific technology for the PV industry in suitable climatic conditions.