Characterization of the building stock in the mountain environment: correlations between natural context, building geometry and energy performance

The identification of reference buildings for building performance simulations is a well-established practice, adopted to reduce the calculation effort, as well as to define new energy refurbishment strategies while retaining the ability to generalize findings to a portion of the existing building stock. The adopted methods to identify these reference buildings usually focus on the building geometrical, material and HVAC system’s properties, relying on either statistical approaches and analyses of panel of experts. Datasets of representative buildings are often correlated with expected building energy performances in typical climate conditions for the region or the country whose building stock they are supposed to describe.

In some regions and territories the identification of reference buildings can be challenging. In the mountain areas, for instance, the role of the specific context in which those buildings are located is fundamental to characterize their energy performance. Indeed, the mountain environment presents a high degree of complexity and variability, in terms of both orographic features and microclimatic conditions.

Consequently, on the one hand, without a proper characterization of the mountain context in which the representative buildings are located, their very function, i.e., being a reference for energy performance analyses, could be undermined. On the other hand, however, complexity and variability of the mountain areas could significantly affect the selection of representative buildings, increasing the number required to allow for a good level of representativeness.

With the goal of finding a proper trade-off, this work presents a preliminary attempt to correlate the morphological and geometrical features of building stock of the mountain regions, as well as its energy performance, to specific geographical characteristics of this environment (i.e., different sky view factor and availability of solar irradiance). To perform this analysis, we focused on the Alpine territory of the Autonomous Province of Bolzano, Italy, and, specifically, on those municipalities belonging to the Italian climate zone F (i.e., with HDD20 > 3000 K d). We analyzed more than 90’000 buildings and, for each, the corresponding sky view factor.

After characterizing the variability of both buildings’ geometrical features and context, a parametric simulation analysis was performed for selected valleys with EnergyPlus, with the aim of discussing the extent to which the mountain natural context can affect the predicted energy performance of representative buildings. Preliminary findings underline different sensitivities of high-performance and uninsulated existing buildings, with the former ones affected by a larger relative uncertainty on simulation outputs.