Uncertainty Analysis of Urban Building Energy Based on Two-Dimensional Monte Carlo Method

Energy performance of urban buildings is affected by a number of inherent uncertain factors, including weather conditions, internal heat gains, occupant behavior, and HVAC systems. These uncertain variables lead to variations of energy use in urban buildings. Therefore, this paper implements a two-dimensional Monte Carlo method to properly assess variations of energy performance of urban buildings by considering two types of uncertain factors (aleatory and epistemic). In this study, aleatory uncertainty refers to inherent randomness of input variables in building energy analysis; whereas, epistemic uncertainty refers to retrofit variations to improve energy efficiency for urban buildings. The results indicate that the two-dimensional Monte Carlo technique can consider two types of uncertain factors to quantify the variations of energy performance in urban buildings. It is also found that the aleatory uncertainty of energy performance is larger than the epistemic uncertainty of energy use in this study, which indicates that more attention should be paid on aleatory uncertainty to reduce its influence on energy use.