A pilot test of Honeywell’s smart building technology has reportedly helped Hamdan Bin Mohammed Smart University in Dubai achieve an initial 10 per cent in energy savings.
A pilot test of Honeywell’s machine-learning-based smart buildings technology has reportedly helped Hamdan Bin Mohammed Smart University (HBMSU) in Dubai achieve an initial 10 per cent in energy savings.
The cloud-based Honeywell Forge Energy Optimisation machine learning solution continuously studies a building’s energy consumption patterns and automatically adjusts to optimal energy saving settings without compromising occupant comfort levels. Honeywell describes the technology as giving buildings "a brain".
HBMSU is the first accredited smart university in the UAE and is known for its technology and innovation programmes.
Honeywell Forge Energy Optimisation was applied to HBMSU’s existing building management system. The additional energy savings are especially significant, claimed Honeywell, because HBMSU is already regarded as a highly smart, energy-efficient building with fully connected lighting, cooling, building management, power and efficiency control that is optimised based on real-time occupancy.
The pilot also uncovered local control issues with the chiller plant and fresh air handling unit that were not adjusting to set points.
“As a smart university, we look to deploy the latest technology across our campus and ensure our buildings are efficient. We were pleasantly surprised by the results we saw from Honeywell Forge and its ability to drive further energy savings beyond our achievable optimisation with the techniques we have,” said Dr Mansoor Al Awar, chancellor of Hamdan Bin Mohammed Smart University.
“Buildings aren’t static steel and concrete – they’re dynamic ecosystems and their energy needs fluctuate based on ever-changing variables like weather and occupancy.”
“Our further partnership with Honeywell will help to support the advancement of artificial intelligence (AI) modelling for building automation and provide our students with first-hand applications of how AI and machine learning will drive operational efficiencies in buildings."
As part of the pilot programme, HBMSU students taking courses like Innovation and Environmental Management will have access to Forge technology.
“Our goal is to collaborate with leading organisations like Honeywell that support our vision of educating the innovators of tomorrow,” said the chancellor.
Energy consumption in commercial buildings is a significant issue because these buildings account for more than 36 per cent of global final energy consumption and nearly 40 per cent of total direct and indirect CO2 emissions, according to figures from the International Energy Agency.
Honeywell Forge Energy Optimisation autonomously and continually optimises a building’s internal set points across hundreds of assets every 15 minutes to evaluate whether a building’s HVAC system is running at peak efficiency.
When Honeywell’s solution finds a need to make an adjustment, it analyses factors such as time of day, weather, occupancy levels, and dozens of other data points to determine the optimal settings per building and makes calculated decisions 96 times per 24-hour period for every building in a portfolio, 365 days a year across the system of assets.
“Our further partnership with Honeywell will provide our students with first-hand applications of how AI and machine learning will drive operational efficiencies in buildings."
Repeated results have shown double-digit reductions of HVAC-related consumption while not impacting customer comfort.
Honeywell claims there is no need to rip and replace systems to add the energy optimisation system to a building.
“Buildings aren’t static steel and concrete – they’re dynamic ecosystems and their energy needs fluctuate based on ever-changing variables like weather and occupancy,” said David Trice, vice president and general manager, Honeywell Connected Buildings.
He added: “With Honeywell Forge Energy Optimisation, we’re evolving building operations far beyond what would be possible even with a robust team of engineers and the rules they code in their building management system.
“By employing the latest self-learning algorithms coupled with autonomous control, we can help building portfolio owners fine-tune their energy expenditures to drive efficiencies and create more sustainable practices for our customers.”
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