Honeywell Forge Energy Optimization is a cloud-based, closed-loop, machine learning solution that continuously studies a building's energy consumption patterns and automatically adjusts to optimal energy saving settings without compromising occupant comfort levels. The solution, says the company, is the first autonomous building solution focused on decreasing energy consumption and may deliver double-digit energy savings, decrease a building's carbon footprint, and can be implemented without significant up-front capital expenses or changes to a building's current operational processes.
"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," says David Trice, vice president and general manager, Honeywell Connected Buildings. "With Honeywell Forge Energy Optimization, 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."
According to reports, energy consumption in commercial buildings accounts for more than 36% of global final energy consumption and nearly 40% of total direct and indirect CO2 emissions. In addition, heating, ventilation, and air conditioning (HVAC) often presents the largest opportunity for energy savings in a commercial building.
Honeywell Forge Energy Optimization autonomously and continually optimizes 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 the system finds a need to make an adjustment, it analyzes 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. Repeated results have shown double-digit reductions of HVAC-related consumption while not impacting customer comfort.
During a pilot at