I've been working with several hospital clients here in Arizona and their ENERGY STAR benchmarking scores don't seem to match what I'm seeing in the field. One 200-bed facility shows a score of 85 (pretty good) but their TEP bills are running $145K/month which seems high for this market. Their kWh/sq ft is about 18.5 which puts them way above peer facilities. Anyone else finding discrepancies between ENERGY STAR ratings and actual utility performance?
Hospital energy benchmarking - ENERGY STAR vs real world
Linda - I see this all the time with healthcare clients. ENERGY STAR benchmarking uses national weather data and doesn't always account for regional utility rate structures. Here in Nebraska, OPPD's demand charges can make a hospital look inefficient even if their actual energy use is reasonable. What's their demand profile looking like? Sometimes the issue is peak shaving, not total consumption.
The other issue with hospital benchmarking is the medical equipment factor. ENERGY STAR can't account for specialty equipment like MRI machines, linear accelerators, or large lab analyzers. I had a Jacksonville client with JEA where their cancer center alone was pulling 400 kW continuously. Skewed all their benchmarks until we created a custom baseline excluding those loads.
Rob, that's exactly what I'm seeing. This facility has a new cardiac cath lab and expanded ICU with high-energy monitoring equipment. TEP's rate schedule GS-21 hits them hard on demand charges during peak hours when all this equipment is running. I think I need to create a custom benchmark that strips out the specialty medical loads and focuses on basic facility operations.
Linda - I've had good success using the California Hospital Association's energy benchmarking data as a supplement to ENERGY STAR. They break down usage by department and equipment type. For Austin Energy clients, I typically see 15-22 kWh/sq ft for general acute care hospitals, but specialty hospitals can hit 35+ kWh/sq ft. Your 18.5 might actually be reasonable depending on services offered.
The weather normalization in ENERGY STAR is definitely wonky for extreme climates. Here in Milwaukee, WE Energies' heating season runs October through April, but ENERGY STAR uses generic national heating degree days. I've seen hospitals with excellent operations get poor scores just because the model doesn't understand Wisconsin winters. Linda, what's your cooling season like in Tucson? That could explain the high consumption.
Linda F - cooling season here basically runs March through October, sometimes November. TEP's on-peak hours are 1-8 PM weekdays during summer months, and this hospital's demand charges spike to $18.50/kW during those hours. Their base facilities probably aren't that inefficient, but the timing of their medical procedures during peak hours kills their cost per sq ft metrics.
I've found that creating facility-specific benchmarks works better than relying on ENERGY STAR for complex buildings. For a hospital client here in Charlotte on Duke Energy's Schedule LGS, I track their performance against their own historical usage adjusted for occupancy, weather, and service changes. More work upfront but gives much better insights for improvement opportunities.
Wayne - that's smart. I do something similar but also benchmark against peer facilities in the same utility territory. OPPD has about 8 hospitals in our service area, so I can create a regional baseline that accounts for local rate structures and climate. Helps identify which facilities are truly underperforming versus just dealing with local utility economics.
This has been really helpful. I think the key takeaway is that ENERGY STAR is a starting point, but regional and facility-specific factors matter way more than the national model suggests. I'm going to work with this hospital to develop custom benchmarks that account for their specialty services and TEP's unique rate structure. Probably will save them $30K+ annually just by optimizing their peak demand timing.
Linda, if you want to share your findings once you finish the analysis, I'd be interested to see the methodology. I'm working on similar projects with Austin Energy hospital clients and could use a good template for custom benchmarking. The specialty medical equipment factor is something I haven't quantified well yet.