OBSERVE: Occupancy-based system for efficient reduction of HVAC energy

TLDR

Heating, cooling, and ventilation account for 35 % of U.S. energy use, yet most buildings condition rooms at maximum occupancy, leading to unnecessary over‑conditioning. The study aims to enable efficient HVAC conditioning by acquiring accurate occupancy information. Real‑time occupancy data from a wireless sensor network are used to build occupancy models that are integrated into building conditioning systems for demand‑control strategies.

Abstract

Heating, cooling and ventilation accounts for 35% energy usage in the United States. Currently, most modern buildings still condition rooms assuming maximum occupancy rather than actual usage. As a result, rooms are often over-conditioned needlessly. Thus, in order to achieve efficient conditioning, we require knowledge of occupancy. This paper shows how real time occupancy data from a wireless sensor network can be used to create occupancy models which in turn can be integrated into building conditioning system for usage based demand control conditioning strategies. Using strategies based on sensor network occupancy model predictions, we show that it is possible to achieve 42% annual energy savings while still maintaining American Society of Heating, Refrigerating and Air-Conditioning (ASHRAE) comfort standards.