Building performance simulation

Calibrating building energy simulation models: A review of the basics to guide future work

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 …

A Total Building Performance Approach to Real-time Occupant Centric Sensing and Control for Mixed Mode Ventilation in the Tropics

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.

An open dataset for the calibration of building energy models

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 HVAC systems

Advanced machine learning based control for the HVAC systems

Epwshiftr: an R package for creating future weather files under climate changes for building energy simulation

An R package for creating future weather files under climate changes for building energy simulation

Life cycle cost optimization

Life cycle cost optimization

eplusr: A framework for integrating building energy simulation and data-driven analytics

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.

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)