A Novel Automatic Method for the Urban Canyon Parametrization Needed by Turbulence Numerical Simulations for Wind Energy Potential Assessment

Abstract

The energy transition to more sustainable forms is currently ongoing worldwide, because of the environmental impacts produced by the non-renewable energy sources employed in the last decades. Among the main alternatives, wind plays a key role and, nowadays, innovative instruments, such as small-scale turbines allow for installation of wind turbines in urban areas. Their energy potential assessment requires high-accuracy simulations of the turbulent flows in the urban canopy layer, which, in turn, require detailed information about the geometrical properties of the basic element to classify urban surfaces, i.e., the urban canyon, often not available. In this work, we propose a novel automatic method, based on Voronoi graph, to univocally identify urban canyons and to extract their geometrical parameters from online available GIS (Geographic Information System) data, and test it on four European cities that differ in size, story and location. Results show the capability of the method to identify the single urban canyon and to properly extract its geometrical parameters, which tend to assume similar values for the largest cities. Moreover, we first attempt to propose and test some curves to generally describe the data probability distribution, which may be useful for turbulence simulations for urban wind energy assessment and planning. The best results are found for the canyon aspect ratio.

Comparing Positioning Performance of LEO Mega-Constellations and GNSS in Urban Canyons

“…Parameter w in London is generated using an exponential distribution with an average of 42 m and a median of 34 m [56]. For Manhattan, a similar distribution for w is assumed.…”

Ventilation in a group of courtyard buildings

“…Badas et al, 2020 [16], Garau et al, 2018 [17], Ferrari et al, 2017 [18]), allowing to extract information about the influence of a single architectural aspect on the outdoor comfort, but without been immediately applicable to the complex nature of urban environment. Recent studies (Badas et al, 2019 [19], Salvadori et al, 2021-a [20] and 2021-b [21]) has allowed to automatically extract the geometrical features characterizing the urban canyons in real cities, via free online available Geographic Information System (GIS) data, so boosting the potentialities of this last approach to describe the urban canopy for atmospheric Fluid Dynamic purposes.…”