ThermoNet: fine-grain assessment of building comfort and efficiency

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Abstract

Understanding the performance of the heating, ventilation, and air conditioning (HVAC) system in large buildings is a prerequisite for optimizing their energy efficiency. Fine grain performance analysis has not, to our knowledge, received adequate attention thus far. To address this issue we evaluate the thermal comfort and the energy efficiency of a relatively modern HVAC system in a large building based on building-wide high-fidelity environmental data collected via a wireless sensor network over 12 months. Access to fine grain information reveals temporal and spatial dynamics that help quantify the level of (non-)compliance with the system’s control objective and the building’s thermal comfort standards: we find over-conditioning at multiple time scales which offers opportunities for reduced operating cost, and identify building anomalies and ill-conditioned rooms that need maintenance. The paper moreover describes ThermoNet, our hybrid wireless sensor network solution for monitoring a legacy building, which uses duty cycling and adaptive power control to achieve high data yield with low power consumption.

Keywords

HVAC system Building Thermal comfort Energy efficiency Wireless sensor network 
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Notes

Acknowledgments

Sincere thanks to: CSE Department staff members Dave Kneisly, Mike Compton, Don Havard and Aaron Jenkins, for helping us deploy ThermoNet in Dreese; OSU Building Automation Services colleagues Kelly Bloomfield, Peter Calamari and Patrick Smith; and OSU Energy Services and Sustainability colleagues Tracy Willcoxon, Gregory Roebke, and Aparna Dial, for sharing control system operation, objectives and utilization data.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2013

Authors and Affiliations

  1. 1.Department of Computer Science and EngineeringThe Ohio State UniversityColumbusUSA

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