Modeling and simulation for predictive building control using high-resolution climateforecasting

The state-of-the-art of building energy management systems uses model predictive control to compare alternative control strategies prior to implementation. Climate conditions dramatically influence the control strategy selection. These rely on conventional climate forecasting that provides coarse resolution with respect to both time and space (e.g. 1 hour, 50 km). The industrial partner Green Power Labs Inc. (GPLI) and Dalhousie University propose to use high-resolution climate forecasting at the sub-hourly and building level resolution (e.g. 15 minute, 5 m) to enhance the accuracy of the forecast utilized in predictive building control. In this project, the Post-Doctoral Fellow, in collaboration GPLI, will carry out advanced building performance simulation to determine the energy/cost/greenhouse-gas-emission performance of such technology applied to a range of commercial buildings in a range of climates. This project will benefit GPLI by defining performance and optimal markets as they rollo-out the new high-resolution forecast and predictive building control technology

Faculty Supervisor:

Lukas Swan

Student:

Partner:

Green Power Labs Inc

Discipline:

Engineering

Sector:

Professional, scientific and technical services; Utilities

University:

Dalhousie University

Program: