The University of Virginia Medical Center chose Affinity Energy to install multi-circuit meters on ATSs around campus. Ultimately, the submeters assist the maintenance supervisor to accurately determine load status during emergency power situations.

University of Virginia Medical Center

The University of Virginia Medical Center in Charlottesville, Virginia, is a Level One trauma center providing both inpatient and outpatient care. It opened in 1901. The facility has a total of 18 emergency generators. 40 ATS, and 15 facility operators.

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Before our ATS submeters, we had zero visibility into our electrical loads. The data I have now gives me the power to mitigate load creep risks and plan for the future emergency power situations of the hospital.

Alex Di Giacomo

Maintenance Supervisor at University of Virginia Medical Center

Challenge

Due to the University of Virginia Medical Center’s exponential growth, it was becoming increasingly difficult for the central energy plant maintenance staff to keep track of electrical loads in their emergency power supply systems (EPSS).

Like many large medical campuses, they have dozens of automatic transfer switches (ATSs) distributed throughout campus. Unlike new hospitals built within the last 10 years, the University of Virginia Medical Center’s 40 ATSs did not have submeters built-in to the digital controllers.

Over its 30-year lifespan, the hospital has undergone rapid growth. Electrical loads have grown and changed, and it was becoming difficult to determine if the loads were growing over original ATS infrastructure load specifications.

The University of Virginia Medical Center needed visibility into potential load creep situations to avoid ATS failure due to lack of supporting capacity.

Solution

Results

By recording the submeter data within their SCADA environment, the University of Virginia Medical Center now has the information to accurately analyze load profiles. Using performance analysis, the maintenance supervisor is able to verify loads prior to ATSs switching to emergency, loads during emergency power situations, and loads after the ATS returns to the normal source.

Using this analysis, it’s simple to identify loads added during a power outage and not removed when normal power is restored. This data will help determine if and where a new generator or ATS capacity upgrade is needed.

After gathering data, the medical center will be able to trend year over year load growth to quantify load creep and prepare the data reports necessary to back up budget requests.