Hybrid Approach for Digital Twins in the Built Environment

Abstract

In recent years, several countries have created policies to enforce Zero Energy Building (ZEB) standards for new building construction. Achieving this for new buildings is feasible, but it may be difficult to transform existing buildings to ZEBs. Digital twins provide a promising approach to monitor existing buildings and further increase their energy efficiency. A digital twin (DT) is a virtual representation of a physical entity. It has several applications in product design, product cycle, and fault detection. This paper presents a hybrid approach that combines physics-based and machine learning methods to create a DT for the built environment. A case study for a digital twin of a single room is also discussed. The initial comparison of cooling energy between the physical testbed and the DT model shows promising results for future development. The limitations, challenges, and future development of the approach are also addressed in the paper.