Dive Brief:
- AI-enabled building management systems can cut building energy use up to 22% compared with traditional controls, according to research published last week by Schneider Electric. That translates into savings of $50,000 per year at current commercial rates, the global energy technology company says.
- By incorporating data from occupancy patterns, weather forecasts, equipment performance and other operational inputs, AI can enable buildings to operate more efficiently while reducing the burden on facility management teams, Schneider says.
- The technology can more than double the energy savings achieved by smart building controls alone, Schneider said in a press release. In addition to cost savings, adding AI to building management systems can save up to 60 metric tons of carbon emissions annually per building, the company says.
Dive Insight:
Buildings remain one of the world’s largest sources of emissions, accounting for approximately 37% of global energy-related carbon emissions, Schneider says.
Many HVAC systems consume more energy than necessary, the company says. Although building conditions, occupancy patterns, equipment performance and operating requirements change over time, control strategies often remain relatively the same, Schneider’s report says.
Conventional building controls don’t adequately address the problem, the report says. Although adding smart controls like building occupancy sensors connected to a BMS can reduce HVAC and lighting demand to drive energy reductions between 10% and 13%, these improvements are insufficient to meet the targeted 20% energy reduction by 2030 called for in many net-zero pathways, Schneider says.
Schneider’s research examined how an AI layer can connect siloed data sources, analyze building conditions and automate HVAC optimization in real time. The paper evaluates the potential for AI-enabled HVAC controls in mid-sized commercial buildings using modeled building performance of a typical office building with three high-performance BMS scenarios.
The modeled results suggest AI can unlock additional efficiency gains beyond the savings achieved by smart BMS. Cloud-hosted AI configuration generated the greatest savings, reducing whole-building energy use by 21.7% to 22.4%, relative to the traditional BMS baseline, Schneider says.
“These results are modeled from the first year of real-world pilot deployments,” Schneider says. “Solutions are expected to improve their performance in subsequent years as the algorithm continues to optimize.”
The company says that small- and mid-sized buildings — those under 100,000 square feet — could significantly benefit from AI-enabled optimization. While energy management systems have historically been too complex or costly for smaller facilities, where dedicated facilities expertise is often limited, AI can help automate and simplify optimization to make sophisticated building management more accessible, the company says.
“AI is putting the power of energy intelligence into the hands of smaller building owners and operators. What once required significant expertise and investment can now be achieved more simply and at greater scale, helping organizations reduce energy waste, lower costs, improve performance, and make smarter decisions with confidence,” Pankaj Sharma, executive vice president of software and services at Schneider Electric, said in a statement.
These improvements mean that implementing AI on building systems can avoid 100 times more carbon than AI system’s own footprint, Schneider says.
