If you could save well over 1,000 metric tons of CO2 and hundreds of thousands of dollars annually while improving your lab’s reliability, would you?

Surprisingly, the answer is often “No.” Because even in labs with optimized HVAC systems, the default mode is “hands off” the air handling units (AHUs). Given the importance of precise environmental controls to product quality and scientist safety, lab facility managers often feel uncomfortable with the idea of intervening in AHUs’ constant high-energy operation — whether that level of output is needed or not. But AHU optimization done right doesn’t degrade safety or reliability; it actually improves key performance measures.

Air quality, freshness and humidity are important in sensitive environments, and an optimization project should give facility operators better control of those factors. The implementation process may also reveal issues that have been masked. For example, a facility may find that its air filtration system also needs an upgrade, and that work can be folded into the AHU optimization project.

Optimization is about running AHUs efficiently, not operating outside lab limits. A comprehensive optimization solution will include system monitoring and alerts that warn facility managers when equipment performance is lagging or problems occur. Ultimately, it will not only save money but also help to prevent unanticipated equipment failures that increase downtime risks.

Hardest-working, greatest savings

Most labs pull 100 percent of their fresh air from outside the building rather than recirculating a portion of it as office buildings do. That means they can’t use economizers, and they need to deliver high air flow through lab areas to keep them safe. These requirements are so energy intensive that optimizing AHUs usually produces a 35 percent reduction in energy use, compared with a reduction of 30 percent for optimizing the rest of the HVAC system.

The biggest savings come from high-use labs that are conditioned 24-7. If the air supply temperature is stuck at one set point regardless of occupancy and activity type, the lab is a good candidate for optimization. Fume hoods also signal opportunity. Facility managers often assume that equipment designed to vent noxious fumes outside the lab — to limit occupants’ exposure — requires a constant fan power and pressure. But fume hoods aren’t in full use most of the time, and they too can be optimized.

As a knock-on effect, AHU optimization also reduces water use. Cooling 100-percent outside air to a constant temperature set point consumes large amounts of chiller energy and causes a lot of water evaporation through the tower. When the set point dynamically adapts to provide the amount of cooling that is actually needed, chilled water usage falls substantially and evaporation losses drop in tandem.

Under the hood

A global manufacturer of optical care products took on AHU optimization at one of its European production facilities despite initial skepticism that there was much to be gained from addressing the AHUs at a site with an already optimized chiller plant and strict air temperature, humidity and pressure parameters. The project moved forward after a high-level go/no-go feasibility analysis, followed by a detailed basis-of-design scoping study, revealed substantial potential savings from optimizing 35 of the facility’s 60 AHUs.

The first priority was to get all of the target AHUs up to modern efficiency standards and prep them for the air-side optimization software. The project team needed to address each AHU individually. For example, some units had broken sensors, some required new variable frequency drives, and most needed tuning to building automation system (BAS) sequences.

With the mechanical upgrades completed, the team installed an AHU-specific optimization solution and integrated it with the BAS. The software, which is connected to a cloud-based measurement and verification platform, provides coordinated control of the two main factors that determine how much energy an AHU consumes: fan speed and air temperature. With continuous optimization of the air handlers to meet temperature, air flow and humidity requirements, the AHUs react dynamically as conditions change, saving energy at both the AHUs and the central chiller plant.

After six months of full operation, the project had reduced overall fan energy consumption by 44 percent and exceeded the original savings projection by 30 percent overall. The site’s energy manager expected the savings to increase over time, and they have: The estimated annual savings were $412,000 and 3.3 million kWh; in the past 12 months, savings were $567,000 and 4.5 million kWh. The project is delivering over 1.4 metric tons of CO2 reduction.

“We’ve been able to step back the speed of the fans, and it’s phenomenal how much we’ve reduced the amount of power they use — from 20 to 50 percent, depending on the unit,” the energy manager said. “We’ve been able to seamlessly achieve the correct temperatures using a lot less energy.”

He also pointed out unexpected improvements in facilities and operations management as a result of the optimization project. Because the fans are moving less air than before, he believes the AHUs’ fans, motors and belts will last longer. And the software alerts managers if temperatures slip or if there’s an equipment failure, like a faulty fan.

Design decisions make a difference

The initial design of air handling systems makes a real difference in long-term energy usage and costs. Combined or hybrid systems, such as a mix of fume hoods and office ventilation, may be cheaper to install but reduce the optimization potential. Separate systems, each focused on its own job, can be controlled individually and you can often be a lot more aggressive about reducing energy use with the air conditioning system than with a system focused on safety.

Another way labs lose out on savings is by assuming that new equipment doesn’t need to be optimized. Even labs designed and equipped for energy efficiency benefit from optimizing control software. Without it, you can end up with efficient equipment running at full speed all the time — that is better than old equipment running at full blast, but not nearly as good as what the new equipment is capable of with advanced controls.

Connectivity is key

One final note on ensuring savings: Without ongoing monitoring, results will start to degrade after about a year or so. A two-way data flow between a facility’s HVAC equipment and BAS and an optimization provider’s network operations center enables real-time monitoring, analysis, maintenance and fine-tuning of the HVAC system. It’s the only way to maintain the efficiencies gained through an HVAC system upgrade.

In the first year after optimization, results may remain constant without cloud connectivity. By the second year, though, the equipment is beginning to age and the facilities team probably has changed settings in the BAS, causing savings to fall off. By the third year without cloud connectivity, a site can lose as much as half of its original carbon and cost savings through natural system performance degradation and operational overrides. Without the external “brain” a cloud connection provides, the falloff can go unnoticed for quite a while, costing the facility thousands of dollars.

With cloud connectivity, you can maintain savings and equip your lab to have even smarter controls in the future. Machine learning and artificial intelligence are poised to enable even better control of HVAC systems. We’re already starting to see companies gain an additional five to seven percent efficiency improvement through machine learning programs added onto their optimization platforms, and there’s more innovation to come.