Ben Erpelding, P.E., Chief Technology Officer at Optimum Energy, speaks to Sustainable Business Magazine about the company’s unique energy management platform and how it has revolutionized the University of Texas at Austin.
Article appeared first in Sustainable Business Magazine
Optimum Energy is a provider of software solutions supported by engineering services which optimize commercial-scale cooling and heating systems, dynamically adapting to changes in the load, weather, and occupancy conditions to save energy and maintain upmost system resiliency.
To deliver scalability, long-term high performance, and efficiency, Optimum Energy developed the OptiCx platform. OptiCx is a modular platform designed to optimize any chilling, heating, or HVAC system. This is achieved through combined software and human components.
One of Optimum Energy’s most prestigious clients is the University of Texas (UT) at Austin, where there is a close relationship between the company and Juan Ontiveros, Associate Vice President for Utilities, Energy, and Facilities Management. “Our holistic approach allows us to optimize the campus chilled water requirements as “one” system as opposed to four independent chilled water plants on a common loop. Using relational controls to optimize the interdependencies between the subsystems brought tremendous results,” explains Mr. Erpelding.
The biggest challenge faced by Optimum Energy at largest scale district systems is moving into a traditionally non-automated sector and introducing automated processes. “Understandably, operators do not want you turning a 5,000-ton chiller on and off automatically,” explains Mr. Erpelding. Optimum Energy has developed both closed loop algorithms and open loop staging to help gain the trust of the operations team. While pumps and towers can automatically control their speeds and sequencing (closed loop control), chiller staging is manual (using open loop control). This is where the benefits of cloud computing can bring additional efficiencies to the project if machine learning coupled with operator dashboards is implemented. “We can show operators graphically when to add and shed chillers,” says Mr. Erpelding. “But, even better, data science can be used to determine what chiller should be added or shed next based on the actual historical efficiency of the equipment and minimum run hours dictated by the owner.”
Having developed a company around the possibility of scaling upwards, Optimum Energy are now looking into scaling in a different direction. “We’re extremely proud of our work with UT Austin, but we don’t just want to do projects for very large customers,” says Mr. Erpelding. “Offices could apply this technology too. The only way to apply these solutions to smaller commercial buildings is being able to provide them at lower cost, so a lot of our research and development now is on how we bring this solution to more markets. More markets for us actually means going down market, which ultimately means being able to offer the same level of energy savings to small facilities and businesses as well.”
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