A digital twin framework for improving energy efficiency and occupant comfort in public and commercial buildings

Anders Clausen*, Krzysztof Arendt, Aslak Johansen, Fisayo Caleb Sangogboye, Mikkel Baun Kjærgaard, Christian T. Veje, Bo Nørregaard Jørgensen

*Corresponding author for this work

Research output: Contribution to journalConference articleResearchpeer-review

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Abstract

Model Predictive Control (MPC) can be used in the context of building automation to improve energy efficiency and occupant comfort. Ideally, the MPC algorithm should consider current- and planned usage of the controlled environment along with initial state and weather forecast to plan for optimal comfort and energy efficiency. This implies the need for an MPC application which 1) considers multiple objectives, 2) can draw on multiple data sources, and 3) provides an approach to effectively integrate against heterogeneous building automation systems to make the approach reusable across different installations. To this end, this paper presents a design and implementation of a framework for digital twins for buildings in which the controlled environments are represented as digital entities. In this framework, digital twins constitute parametrized models which are integrated into a generic control algorithm that uses data on weather forecasts, current- and planned occupancy as well as the current state of the controlled environment to perform MPC. This data is accessed through a generic data layer to enable uniform data access. This enables the framework to switch seamlessly between simulation and real-life applications and reduces the barrier towards reusing the application in a different control environment. We demonstrate an application of the digital twin framework on a case study at the University of Southern Denmark where a digital twin has been used to control heating and ventilation. From the case study, we observe that we can switch from rule-based control to model predictive control with no immediate adverse effects towards comfort or energy consumption. We also identify the potential for an increase in energy efficiency, as well as introduce the possibility of planning energy consumption against local electricity production or market conditions, while maintaining occupant comfort.

Original languageEnglish
Article number40
JournalEnergy Informatics
Volume4
Issue numberSuppl. 2
Number of pages19
ISSN2520-8942
DOIs
Publication statusPublished - Sep 2021
Event1st Energy Informatics.Academy Conference Asia - Sino-Danish Center Sustainable Energy, Beijing, China
Duration: 29. May 202130. May 2021
Conference number: 1
https://www.energyinformatics.academy/eia-asia-2021-conference

Conference

Conference1st Energy Informatics.Academy Conference Asia
Number1
LocationSino-Danish Center Sustainable Energy
Country/TerritoryChina
CityBeijing
Period29/05/202130/05/2021
Internet address

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