Building energy simulation (BES) plays a significant role in buildings with applications such as architectural design, retrofit analysis, and optimizing building operation and controls. There is a recognized need for model calibration to improve the …
This research has a total project value of S$3.75 million and is supported by the National Research Foundation Singapore under its Cities of Tomorrow R&D Programme, and administered by the Building Construction Authority.
Building energy modeling has become more widely used for building performance assessment and building regulations compliance. The energy model of the SinBerBEST Cyber-Physical Testbed provides a straightforward “virtual testbed” platform for evaluating the performance, efficiency, and effectiveness of technological innovations.
However, before using for technological assessments, the testbed model itself should be calibrated using in-situ experiments from various operating conditions to ensure it reasonably follows the testbed’s real thermal and energy performance.
Advanced machine learning based control for the HVAC systems
An R package for creating future weather files under climate changes for building energy simulation
Life cycle cost optimization
A framework for seamless integration between Building Energy Simulation (BES) and data-driven analytics.
Generating certified energy models in Singapore through an M&V framework.An NUS project in collaboration with Professor Godfried L. Augenbroe (Georgia Institute of Technology)