Seasonal effects of input parameters in urban-scale building energy simulation

Abstract

Urban Building Energy Models are powerful tools for estimating future states of energy consumption and energy generation in buildings. Due to the complexity of these systems, large amounts of data are required, which are often incomplete or unavailable. Through the implementation of building archetypes, models such as the City Energy Analyst minimize the amount of input data. However, these simplifications inherently increase the uncertainty of the expected results.

This paper presents a sensitivity analysis of architectural properties (window-to-wall ratio, occupant density and envelope leakiness), thermal properties (U-values, G-values, thermal mass and emissivity of building surfaces), operating parameters (set point temperatures and ventilation rates) and internal loads (heat gains due to occupancy, appliance use and lighting). For this, the study combines a two-step process of sensitivity analysis with Saltelli's extension of the Sobol method and the City Energy Analyst. The methodology is applied to a case study area in central Zurich, Switzerland, comprising 284 buildings with predominantly educational, hospital and residential uses.

The results showed that the cooling demand in the area was very strongly influenced by the set point temperature, with other variables having a relatively minor influence. For the heating case a larger number of variables were needed in order to explain variations in demand, primarily the thermal properties of the envelope and air exchange rates of the buildings. This was generally true for all occupancy types, shapes, sizes and locations, showing the importance of accurate estimates of these parameters in urban building energy modeling. On a broader sense, the results contribute to the development of urban energy simulations that are both practical and accurate.