Building analytics software helps facilities managers and other professionals stay abreast of what’s happening at any time. In addition to alerting them to problems such as faulty machinery or security breaches, these platforms can pave the way for significant energy savings. Such gains are especially welcome as many decision-makers seek the most effective ways to meet emissions targets.
Improved response to changes
People often encounter drift-related obstacles as they use building analytics software to improve energy usage metrics. Drift occurs due to the aspects over which there is little or no control during an energy-optimization process. They include people manually overriding temperature settings due to discomfort, HVAC components gradually failing and making systems operate less efficiently, or tenants moving in and out of office buildings.
However, many analytics tools integrate artificial intelligence (AI) and can automatically adjust when those events occur. Depending on the types of sensors in use, this hardware can detect when a climate control system’s parts are about to fail—even before the symptoms become obvious to humans.
One type of commercially available software that uses AI collects data about a building and its sensors every five minutes, using that information to construct room-by-room models for energy usage. After the software’s learning period, it’s 99% accurate in its predictions of what will happen in each room over the next six hours.
Even the most conscientious and observant facility managers can’t react to all the various changes associated with the buildings they oversee. Many commercial buildings have hundreds of assets that could collectively alter the overall energy used. Fortunately, AI learns from data exposure and can respond quickly to different variables. There’s a larger probability of higher energy savings gains, even if many things fluctuate throughout a typical day.
Many professionals in the energy industry use automation to find and resolve issues or otherwise improve their processes. Facility managers can do something similar by letting AI-powered tools automate some of their decision-making needs. Although artificial intelligence should not replace human oversight, it can supplement it.
Informed decision-making
Building analytics tools are fantastic for showing decision-makers which appliances, processes, floors, or rooms use the most energy and why. The results are often surprising. For example, lights comprise about 12% of the commercial building sector’s energy usage. The data from an analytics platform could encourage a building manager to switch to energy-efficient bulbs or fixtures, for example.
Another option is to use lights with motion sensors that automatically turn on or off as people enter or leave a room. That approach prevents issues where someone may accidentally leave lights on overnight or through the weekend if they’re the last person to leave a room.
Once leaders see the hard data, they may realize the best option is to invest in newer, less energy-intensive equipment. Heating and air conditioning systems are often among the biggest power consumers in commercial buildings. Switching to newer models could bring noticeable benefits. Getting the statistics from building analytics platforms can motivate owners to decide it’s time for change.
After facilities managers see the potential results of targeted changes, they may go further by getting their buildings certified for energy efficiency. For example, the EPA’s ENERGY STAR certification for commercial buildings allowed participants to save 230 billion kilowatt-hours of electricity annually.
Information associated with the program indicates commercial buildings account for more than half of the U.S.’s annual energy consumption, costing more than $300 billion per year—more than any other economic sector. Additionally, more than 30% of that used energy frequently gets wasted due to inefficiencies.
The EPA offers free building analytics software to help ENERGY STAR program participants measure, benchmark, and track a building’s energy usage. However, any tools facility managers currently use could likely produce similar results.
Detailed insights into renovation-related options
Many people use analytics tools to improve fully constructed buildings’ performance and resource usage. That’s an understandable and accessible option. However, as the Swedish DecarbonAIte project shows, opportunities also exist to curb unnecessary energy usage and achieve other gains by analyzing choices made during the renovation process.
The researchers involved identified numerous challenges, such as inaccuracies and uncertainties in building models that can make those resources less valuable than anticipated. Additionally, the so-called energy-efficiency gap can result in seemingly cost-effective solutions not being the optimal solutions in real life. Such issues can persist until future renovations occur, especially since shortcomings are not necessarily evident until a project’s completion.
DecarbonAIte uses AI to make automated and minimally invasive but thorough assessments of thermal statistics associated with buildings that will soon be renovated. In one of the project’s case studies, the researchers used building analytics software to take energy usage readings before and after the renovation. The structure was a four-story residential building with a basement.
Renovations occurred in 2020 after decision-makers decided to reduce heating-related demands. The enhancements included improving the insulation in the walls, floor, and roof, as well as replacing the windows. However, before making any changes, the participants created a database of all the costs and embodied carbon of each potential renovation material.
Next, they made building simulations focusing on the most uncertain aspects, such as air tightness. The models also included details about the materials used, a building’s energy needs, and the planned renovations’ effects. The researchers conducted 698 simulations during this project that revealed which parameters had the greatest impact on energy usage. Such insights allowed parties with authority to select which renovations to proceed with for the most meaningful results.
Building analytics software provides better oversight
The main reason building analytics software is so valuable for raising energy savings potential is that it helps the relevant parties know and respond to changing conditions at any time. Surprise energy bills often arrive when people have little or no knowledge about how much electricity and other resources their buildings use in a typical day or month.
When those individuals can track historical insights through building analytics software, they can quickly notice abnormalities and address the root causes. However, anyone considering this approach should be thoughtful and careful while proceeding.
A good starting point is to identify which building assets to monitor, whether lights, HVAC systems, or automatic doors. All could influence overall energy usage, but understanding why is critical to making gains. For example, does the building unnecessarily use energy because too many people forget to turn off lights after leaving the room?
Perhaps the bigger culprit is the temperature settings in the building to keep people comfortable. Many occupants ultimately realize that adjusting the thermostat by a few degrees in favor of energy efficiency won’t cause the expected discomfort, so they agree it’s a good idea.
Examining building analytics helps owners and facility managers acquire the knowledge needed to justify specific changes and set relevant goals.
Related article: Is AI an energy efficiency game changer for older buildings?
