Science

This IIT Mandi algorithm can help buildings save money and energy

TV Jayan New Delhi | Updated on March 19, 2020 Published on March 19, 2020

Researchers have, through simulation studies, designed a software tool that can diagnose failure in heating, ventilation and air conditioning components Researchers have demonstrated the effectiveness of the algorithm

 

People working in huge office buildings or spending time in multi-storeyed malls may have sometimes felt that certain areas of the building were warmer or cooler than the rest. This happens mostly because of local faults that occur in climate control systems, which are technically described as heating, ventilation and air conditioning (HVAC) systems.

Apart from causing discomfort to the occupants, a faulty component may hamper efficient operation of HVAC and increase operation costs. It can also increase the load on the other healthy components, leading to increased wear and tear and reducing the life of the entire system.

Diagnosing failure

But now, there could be an easy way to detect such defective parts in complex HVAC systems with researchers at the Indian Institute of Technology (IIT) Mandi in Himachal Pradesh designing an algorithm that can diagnose failure in HVAC components.

The software tool — described in the Journal of Building Engineering this month, by Tushar Jain, an assistant professor at IIT Mandi’s School of Computing and Electrical Engineering; his research student Mona Subramaniam and their French collaborator, Joseph Yamé from Universitè de Lorraine — could be a boon to the multi-billion dollar HVAC industry in the country. Indian HVAC market is said to be growing at a CAGR of 7 per cent and is expected to touch $5.9 billion by 2024.

HVAC systems, which are now commonplace, account for more than half the energy consumed by commercial sector buildings. While no data is available for India, studies in the US have shown than energy wastage due to 13 most commonly occurring faults in climate control systems is between 32 and 171 billion units a year.

In centralised HVAC systems in buildings, climate control and ventilation are performed at a centralised location outside the building by an air handling unit. The processed air is then distributed to every room with the help of controlled ducts and excess air in the room is recirculated through the unit. One key component of such climate system is variable-air-volume (VAV) terminal boxes, which allow each room to individually control the cooling or heating. VAV systems allow zoning within the building, and making it comfortable for occupants in each zone, taking into consideration a host of factors, including number of occupants in the room, etc.

According to the researchers, commercially-available building energy management systems cannot accurately pinpoint the location and magnitude of fault that has occurred in the HVAC. As a result, even though automatic diagnosis of faults can provide a heads-up on possible failure, leading to proactive repairing of the system, it is not currently available.

Effectiveness of algorithm

To do this, Jain and his colleagues focussed on a component of VAV system called VAV damper. The damper, which adjusts its position to increase or decrease air flow to the room, can be used as an indicator of any faults or failure that occur the VAV system. Timely and automatic detection of faults in these components can be very useful in managing the health of the HVAC, said Jain.

IIT Mandi team, one of the few public-funded research groups working on this problem, has demonstrated the effectiveness of the algorithm through exhaustive simulation studies. As the next step, they hope to conduct real-time testing and validation using it on a real building monitoring platform.

Jain said any organisation that would like to use the tool can add this existing building management system software. If floor plan of the building is available, the process can be easily automated and bootstrapped, he said adding that this could be retrofitted to the existing systems as well.

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Published on March 19, 2020
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