Towards occupant-driven district energy system operation

A digital twin platform for energy resilience and occupant well-being

Conference paper (2022)

Authors

M.A. Mosteiro Romero National University of Singapore

Pradeep Alva Singapore-ETH Centre, National University of Singapore

Clayton Miller National University of Singapore

Rudi Stouffs National University of Singapore

Affiliation

External organisation

Digital twins Energy resilience Urban building energy modelling Occupancy modelling

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Published Date

2022

Language

English

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Abstract

This paper presents a digital twin of a university campus in Singapore as a demonstrator for a digital-twin enabled approach to district energy resilience. This paper focuses mainly on the development of the building energy and occupancy models in the digital twin, which are complemented by a user interface for real-time data visualization and scenario assessment. The building energy demand model of the case study area was calibrated using measured hourly cooling and electricity data collected in the case study area. Occupant presence was estimated using WiFi connection counts, and a simple regression model was developed to assign electricity loads as a function of occupant presence and time of day. The digital twin’s scenario assessment capabilities were explored through scenarios on the long-term effects of climate change and of the increase of remote working and studying as a result of the COVID-19 pandemic. Four different “work-from-home” cases were considered, and three different building operation strategies were assumed for each case. The results show that a decrease in building occupancy post-COVID-19 would lead to minimal space cooling savings in the case study area unless building operation was proactively adjusted to adapt to the new needs of the campus.