AI-Powered HVAC Systems: A Step Toward Energy Efficiency in Buildings
Image Credit: Sigmund | Splash
Heating and cooling buildings accounts for 18% of global energy use, according to the International Energy Agency. Many structures rely on outdated HVAC (heating, ventilation, and air conditioning) systems that struggle to adjust to weather changes, leading to notable energy losses. Researchers and technologists are exploring artificial intelligence as a potential tool to improve building efficiency, even as concerns persist about AI’s own energy demands.
AI’s Dual Role
AI’s development has drawn scrutiny for its power consumption—Microsoft, for instance, has noted that its AI efforts have complicated its climate targets. Yet, some experts suggest AI could also help reduce energy use. A 2024 study from Lawrence Berkeley National Laboratory estimates that AI integration in buildings could lower energy consumption and carbon emissions by at least 8%, with greater reductions possible alongside strong policy support. Initial applications of AI in HVAC systems are showing positive results, hinting at broader potential.
Nan Zhou, a senior scientist at Lawrence Berkeley and co-author of the study, highlights AI’s broader possibilities. “To date, we mostly use AI for our convenience, or for work”, she says, “but I think AI has so much more potential in making buildings more efficient and low-carbon”.
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A Case Study: 45 Broadway
One example is 45 Broadway, a 32-story office building in Manhattan, built in 1983. Previously equipped with basic thermostats, the building faced inefficiencies due to its lack of weather-responsive controls, says Avi Schron, executive vice president at Cammeby’s International, the property’s owner. New York City’s Local Law 97, passed in 2019 to enforce emissions limits, prompted Schron to adopt an AI system from BrainBox AI, a startup focused on building optimization.
BrainBox AI’s technology collects real-time data from sensors monitoring temperature, humidity, sunlight, wind, and occupancy, then adjusts HVAC settings accordingly. “I know the future”, says CEO Sam Ramadori, describing how the system issues thousands of instructions every five minutes to manage equipment like pumps and fans. For example, it preheats the building before a cold spell or reduces heating on sunlit sides. After 11 months, 45 Broadway reported a 15.8% reduction in HVAC energy use, saving over $42,000 and cutting 37 metric tons of carbon emissions. Schron notes improved tenant comfort and a straightforward installation process, calling it “found money” that also aids the environment.
BrainBox AI now manages HVAC systems in 4,000 buildings worldwide, from small stores to airports. The company plans to introduce Aria, a generative AI assistant, in early 2025, allowing facility managers to control systems via voice or text.
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Scientific Support and Global Examples
Research reinforces these outcomes. Zhou’s team at Lawrence Berkeley projects that AI could reduce building energy use and emissions by 8% to 19%, affecting design, construction, operation, and maintenance by anticipating equipment issues and refining performance. Zhou also suggests AI-managed buildings could support power grids by adjusting energy use to match the fluctuations of renewable sources like solar and wind.
Other efforts show similar promise. In Stockholm, AI tools in 87 educational facilities cut annual carbon emissions by 64 tons and electricity use by 8%, per a recent study. The University of Maryland’s Center for Environmental Energy Engineering found that AI’s predictive features could lower power use in complex HVAC setups. Arash Zarmehr of WSP, an engineering firm, views AI adoption as “a necessary move” for reducing building emissions, noting that manual controls often limit efficiency.
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Obstacles and Concerns
AI’s application in building efficiency faces challenges, including tenant data privacy and system safety. More broadly, AI’s environmental impact is under review. The International Energy Agency predicts that data center electricity demand, largely tied to AI, could double from 2022 to 2026. A recent study from the University of California Riverside and Caltech cautions that air pollution from AI-related power plants could contribute to 1,300 premature U.S. deaths annually by 2030. “It’s a public health issue we need to address urgently”, says co-author Shaolei Ren.
Some critics contend that highlighting AI’s green applications might overshadow its wider ecological costs, a concern dubbed greenwashing. Zhou recognizes this issue, noting that AI data center energy use has grown since her research began. She believes AI’s benefits still outweigh its downsides but calls for further study to assess its overall effect.
Source: Time, Yahoo! News, BrainBox AI, Bloomberg, Urban Green Council, Nature
