Wireless Sensors Bring ‘Smart’ HVAC, Safety

Tuesday, April 19, 2011 @ 04:04 PM gHale

Real-time occupancy sensors and computer algorithms can help create “smart” heating, ventilation and air-conditioning (HVAC) systems.

Based on early test results, the software- and sensor-based solution produced electrical energy savings of between 9.54 and 15.73 percent on their test deployment on one floor of a 5-floor campus building.

“It’s clear that sensors and computing are key to reducing the demand for electricity in office buildings,” said Yuvraj Agarwal, a research scientist at the University of California, San Diego’s Computer Science and Engineering (CSE) department. “Based on the test deployment, we estimate 40-50 percent in energy savings if we deployed our system across the entire CSE building. This is a significant real-world energy saving that comes while maintaining important quality-of-life measures related to building availability, lighting, comfort and appearance.”

In the continuing effort to eliminate costs in operations, manufacturers need to continue finding areas to reduce costs. Studies continue to show buildings account for nearly 40 percent of primary energy use in the United States, and three-quarters of that consumption is electrical—half in residential buildings, half in commercial. HVAC systems are a prime target to increase energy efficiency and reduce costs.

“Rising energy costs and damage to the environment have made scientists focus increasingly on major contributors to that consumption in the belief that even small improvements can translate into large overall savings,” said Rajesh Gupta, a co-author of a research paper and associate director of the UCSD division of the California Institute for Telecommunications and Information Technology (Calit2). “We focused initially on computing infrastructure, and that led us to thinking about how to use computers to improve the efficiency of existing systems that regulate when HVAC systems go on and off in buildings.”

Gupta, Agarwal and their colleagues looked at their CSE building where the HVAC system accounts for between 25 and 40 percent of total annual electricity load. Like in most commercial buildings, the campus Energy Management System sets HVAC systems on a “static occupancy schedule,” which means the systems times itself to coincide with standard working hours (for the CSE building, from 5:15 a.m. to 10 p.m. on weekdays).

This occurs because there is currently no easy and cost-effective way of knowing when individual occupants arrive in or leave their offices.

“The static control algorithm is relatively primitive and it results in a lot of wasted energy during periods of low occupancy,” said Agarwal. “Our solution is a novel control architecture that uses a network of sensors to keep track in real time of which areas of the building are occupied.”

To test their system, the researchers deployed an occupancy sensor network across an entire floor of the CSE building.

The sensors detected several periods of low occupancy when HVAC systems were operating at full steam – and therefore wasting energy. Working with administrators of the campus EMS, the researchers used the real-time occupancy information from each sensor node to turn the floor’s HVAC systems on or off. The “aggressive duty-cycling” of HVAC systems saved energy while still meeting building performance requirements.

The cost of sensors and their deployment is a significant barrier the team overcame with an in-house design that brought the cost of the sensor to below $10 – one-tenth the price of the cheapest commercial sensor. At that cost, the sensor network can make widespread monitoring and control possible inside buildings.

Instead of simply using passive-infrared (PIR) movement sensors (which are typically used to turn on lights when someone is detected entering an area), the UCSD experiment combined a PIR sensor with a magnetic reed switch. A small magnet goes on the door so when the door is closed, the magnet and reed switch become adjacent, thus detecting when a door is open or closed. In testing, the combined occupancy sensor was accurate 96 percent of the time, with minimal false positives.

There were no false negatives during the testing phase, which means it didn’t detect someone’s presence when they were there. The novel sensor nodes can detect occupancy, but the same sensors could also include a safety mode to count people or detect environmental parameters such as temperature, humidity, and light levels, among others.

To see use in all types of new and existing buildings, “these occupancy sensors must be wireless and low power so that they are cost effective to deploy and can run on batteries for several years,” Agarwal said.

In addition to the design and implementation of a low-cost and high-accuracy wireless occupancy sensor node, the researchers designed a control architecture to actuate individual HVAC zones based on occupancy information.

The sensors connect to a wireless module and base station, which send the information to a database and computer server that analyzes the sensor data.

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