Estimating building electricity performance gaps with internet of things data using Bayesian multilevel additive modeling

Chang, S; Castro-Lacouture, D and Yamagata, Y (2020) Estimating building electricity performance gaps with internet of things data using Bayesian multilevel additive modeling. Journal of Construction Engineering and Management, 146(12): 05020017, ISSN 0733-9364

Abstract

Energy models should be simplified to handle data limitations and should predict reliable energy use. Currently, it remains challenging to ensure an appropriate level of detail for simplifying building energy models and to avoid performance gaps when predicting electricity consumption. In this respect, this research proposes to identify an appropriate level of simplifying a building energy model, predict electricity demands and performance gaps using the simplified energy model, and expand the model usability through the operational stage. Building electricity demands predicted through EnergyPlus (version 8.7.0) simulation are compared with actual electricity data collected through Internet of Things (IoT) sensors. Consideration of performance gaps increases the predictability of electricity consumption of a simplified energy model. Also, the Bayesian multilevel additive model updates the performance gaps along with the collection of new IoT data. The findings of this study contribute to forecasting electricity demands with a simplified energy model by predicting performance gaps that can be applied to predicting the electricity needs of similar buildings in the design stage and controlling operational electricity use in the operational stage by comparing sensor measurement with reference data provided by the energy model.

Item Type: Article
Uncontrolled Keywords: internet of things; monitoring energy model; performance gaps; planning building energy
Index terms: performance gap, design stage, building energy model, estimating, electricity demand, level of detail, usability, monitoring, internet, modelling, energy use, electricity consumption, forecasting, energy model, energyplus
Subjects: performance management, professional practice, environmental science, energy systems, financial and cost management, analytical methods, prediction and forecasting, technical documentation, control systems, computing systems, user-centered design
Topics: Site Management, Quality Management, Digital Applications, Design Practice, Sustainability, Engineering Principles, Research Practice, Cost Management
Descriptive scope: 3 PCA

N.B. Descriptive scope is a count of how many of the five facets of empirical research are indicated by the words used in title, abstract and keywords. It is not intended as a judgement on the research; merely a count of the kind of word we would expect to indicate Phenomenon, Concepts, Theoretical framing, Empirical techniques, Analytical techniques. If all five are present, then a code of “5 PCTEA” will indicate this. If you feel the coding for this record is questionable, we welcome discussion around the terms we matched or the way we categorized them. The facet you would expect may not be coded, or a facet may be coded inappropriately. This can also bear on a larger question, of which facets should be treated as defining in construction management research. Please get in touch, and we will look at it. More details here