Uncertainties in energy consumption introduced by building operations and weather for a medium-size office building

Abstract

Deviations between predicted and actual building energy consumption can be attributed to uncertainties introduced by four components of such projections: (1) the accuracy of the underlying models in simulation tools, (2) the accuracy of input parameters describing the design conditions of building envelope and HVAC systems, (3) actual weather, (4) variations in building operation practices. This study investigates uncertainties in energy consumption due to actual weather and building operational practices, using a simulation-based analysis of a medium-size office building. The combined effect of poor practice in building operations across multiple parameters results in an increase in energy use of 49-79% across four selected cities, while good practice reduces energy use by 15-29% across the cities. The impact of year-to-year weather fluctuation on energy use ranges from -4% to 6%. To determine the uncertainty distribution profile for annual energy use, a Monte Carlo method is applied to sample the possible combinations. This study finds that the uncertainty distribution in annual energy consumption approximately follows a log-normal distribution, and shows that the uncertainty range due to operational factors even at an 80% confidence level can dwarf the impact of design features.

A Review of the Regulatory Energy Performance Gap and Its Underlying Causes in Non-domestic Buildings

“…Kleber and Wagner (2007) monitored an office building and found that failures in operating the building's facilities caused higher energy consumption, and they underline the importance of continuous monitoring of a building. Wang et al (2012a) showed that poor practice in building operations across multiple parameters results in an increase in energy use of 49-79%, while good practice reduces energy consumption by 15-29%. Piette et al (1994) suggest that building operators do not necessarily possess the appropriate data, information, and tools needed to provide optimal results.…”

“…According to Bhandari et al (2012), the predicted annual building energy consumption can vary up to 7% as a function of the provided location's weather data. While Wang et al (2012a) showed that the impact of year-to-year weather fluctuation on the energy use of a building ranges from −4 to 6%. Knowing the uncertainty of related microclimate variables is necessary to understand its impact on energy prediction (Sun et al, 2014).…”

Multi-year and reference year weather data for building energy labelling in north Italy climates

“…Eventually, typical years are also necessary for assessing the building energy performance under standard weather reference conditions, which are expected to be representative of the multi-year series in a given location. Some previous studies observed that the variability of buildings annual energy uses are less than 10 % in the multi-year period -between 4 % and 6 % for U.S. climates [8,9] or 4.6 % for Hong-Kong [10]. Although the previous studies are valid only for the climatic context and buildings analysed, they indicate that a single reference year can generally be used to express the typical energy performance.…”

Impact of Human Actions on Building Energy Performance: A Case Study in the United Arab Emirates (UAE)

“…Prior to proceedings, it is important to highlight that the literature lacks a standard on the design of parametric variation experiments, in particular, the choice of the ranges over which to vary each parameter. Consequently, the authors adopted a conservative approach by using ranges that are smaller than or equal to those used in previous comparable studies [25,26,42]. This ensures that the variations simulated in this study are in line with previously published work on the topic, which helps confirm the validity of the experimental design.…”