Partitioning Climate, Users, and Thermophysical Uncertainties from Building Energy Use: A Monte Carlo &amp; ANOVA Approach

Hamed Yassaghi,Jin Wen,Simi Hoque,Nariman Mostafavi

doi:10.3390/buildings12020095

Abstract

Buildings are subject to many uncertainties ranging from thermophysical performance to user activity. Climate change is an additional source of uncertainty that complicates building performance evaluation. This study aims to quantify the share of uncertainties stemming from building factors, user behavior, and climate uncertainty from boilers, chillers, fans, pumps, total HVAC systems, and total site energy use. A novel method combining Monte Carlo analysis and ANOVA is proposed to partition uncertainties from building energy simulation results under different climate change scenarios. The Monte Carlo method is used to generate distributions of building and user factors as building simulation inputs. Then, simulation results under current and future climate conditions are post-processed using a three-way ANOVA technique to discretize the uncertainties for a reference office building in Philadelphia, PA. The proposed method shows the share in percentages of each input factor (building, user, and climate) in the total uncertainty of building energy simulation output results. Our results indicate that the contribution of climate uncertainty increases from current conditions to future climate scenarios for chillers, boilers, fans, and pumps’ electricity use. User parameters are the dominant uncertainty factor for total site energy use and fans’ electricity use. Moreover, boiler and HVAC energy use are highly sensitive to the shape and range of user and building input factor distributions. We underline the importance of selecting the appropriate distribution for input factors when partitioning the uncertainties of building performance modeling.

Highlights

In the United States, buildings are major consumers of energy, with commercial buildings accounting for 18% of the total national energy use [1]
Uncertainties shift from an equal share of building and user factor contributions (Figure 5) to a more user dominant uncertainty in the second scenario (Figure 8)
Similar to the first scenario, the share of climate uncertainty increases for chiller electricity and boiler gas from current conditions to the end of the century

Summary

Introduction

In the United States, buildings are major consumers of energy, with commercial buildings accounting for 18% of the total national energy use [1]. The energy performance of commercial buildings is impacted by building thermophysical factors, occupant behavior, and exterior climate conditions [2,3,4]. Emissions scenarios provide snapshots of climate variability over time and are used as inputs for climate models [11]. These climate models are coarse in resolution and need to be downscaled before they can be incorporated into building simulation tools [12,13]. Climate models and emissions scenarios are uncertain in their nature [14] and downscaling them adds to this uncertainty [15], further complicating building energy modeling under uncertain thermophysical factors and user behaviors

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Results

Conclusion