The interview begins with an assessment of opportunities for optimizing institutional chiller plants. McColly notes that the U.S. Energy Information Administration reported last year’s commercial and institutional energy consumption for cooling was 154 billion kWh. This represents 4% of the total energy expenditure in the U.S.  Recognizing that energy consumption is both climate- and economy-driven, McColly emphasizes that we’ll continue to see more cooling technology added globally, and his goal is to make associated energy savings more proactive than reactive. Improving equipment and sequences—and adding an optimization layer to large chiller plants—presents a significant opportunity for energy savings.

When asked about the day-to-day challenges he sees related to maintenance and operations, McColly shared that it’s becoming more difficult for businesses to keep trained personnel on staff. Linked to this is a reduction of young skilled labor coming into the industry. His hope is that the data science industry—which is gaining significant interest with high schoolers engaged in STEM studies—can help overcome some of the loss of skilled personnel.

When asked whether he sees a role for artificial intelligence (AI) and machine learning (ML) in this space, McColly said that it’s absolutely mandatory. As skilled professionals retire from maintenance and operations roles, we can bridge the gap with AI and ML tools. He emphasized that it’s not about replacing jobs. Rather, it’s a genuine interest in solving problems and reducing energy footprints, and these tools augment the ability of maintenance and operations professionals to do their jobs.

Another industry challenge McColly sees is the difficulty of selling energy efficiency projects. If they’re not tied to carbon reduction or energy efficiency goals, such projects are hard to promote because they’re more expensive than what code requires. With growing concern about climate change and indoor air quality, however, we’ll see incremental improvements of base standards, and “advanced” programs will eventually become normal practice.

Asked about the gains that can be achieved with optimization of chiller plants or HVAC systems, McColly shares three impressive case studies. The first features a higher education campus in a warm climate that saved 21 million kWh per year by optimizing its chiller plant, resulting in an 18% reduction in campus-wide energy usage. Another example is an educational institution in an extremely hot and cold climate saving nearly 15% of campus electricity through chiller optimization and upgrades. A third educational institution in the south saved 17.5 million kWh per year, representing a savings of 14%.

The paybacks for such projects are usually very fast because the savings are perpetual, and there’s quite often more savings opportunity available through support channels, along with additional data and analytics.

McColly discusses digital twins and their role in making systems more reliable. Far beyond the old standard of having a schedule of equipment on a piece of paper, digital twins can be an important factor in troubleshooting. They can also facilitate a whole new level of visualization by complementing augmented reality (AR) technology.

As owner of Cascadia Sustainability Engineering, McColly consults with clients about asset management and how to use data to achieve more efficient facilities operations. He helps businesses realize a new level of maturity—focusing on efficiency, awareness of what they have, what they’re spending money on, when equipment needs to be replaced, and more. He notes that it’s remarkable what can be overlooked if someone is just focused on maintenance or repair. With visibility into runtime data, and insight into how to read the data, organizations can proactively achieve greater equipment reliability and global energy savings.