What the Energy Efficiency World Can Learn from Winter Storm Juno
As I awaited the ‘historic’ blizzard in my central New Jersey apartment, I went over my preparedness checklist in my head. Car tucked away from the street, check; all of my electronics charged, check; enough food, water, and flashlights for a few days of “roughing it,” check, check, check. The hours ticked by. “Any minute now”, I thought.
Fast forward to Tuesday morning. My anticipation quickly turned into disappointment. I had prepared for a blizzard, and although I probably should have been relieved that the conditions were not dire, I was honestly let down. Where was all the snow?! I had studied the weather reports, watched public transit as it was preemptively shut down, and heard our Mayor De Blasio declare it “one of the largest storms in the city’s history.” So what gives?
It turns out that despite huge strides in recent years, weather is still one of the most difficult things to predict. Forecasting the weather involves taking into account variables such as temperature, pressure, wind speed and direction, clouds, precipitation, and that’s just the beginning. Throw in ground temperatures, sea temperatures, ocean currents, sea ice, and the effects of climate change, and the weather models still tax our best super computers and meteorologists.
This notion of unpredictability is also applicable to the field of energy efficiency. Take my day-to-day work where I spend my days analyzing the energy data of buildings. I have all of this great data, from physical building attributes to energy consumption to completed energy-saving retrofits. With this I can create very useful predictions and models, but occasionally the actual energy usage at a building charts its own course.
Why?
Just like in meteorology, there are outside factors that contribute to the unpredictability of energy models. Retrofits are installed by real people, equipment is run by real people and these buildings are occupied by, you guessed it, real people. Simply put, there is no energy model that accounts for all aspects of human behavior.
Luckily, unlike meteorologists, we do not have to sit back and just observe as the storm unfolds (or doesn’t….sigh). While we might not be able to predict the unpredictable in buildings, we can monitor it and respond with corrective action in real time. It is a sad fact that even the best energy efficiency projects can fall victim to “energy creep,” where retrofits show savings for the first few months, then slowly creep back to their pre-retrofit inefficiencies. Thankfully, with the advent of smart meters, sensors, and the “internet of things” we can see when this is happening in time to fix it.
This proactive technology is the equivalent of a meteorologist being able to bend Mother Nature to their will. While this ability might sound like complete and utter magic in the world of weather forecasting, for buildings it just requires care, diligence and the experience of knowing what to do when the building veers off course. It is magic we do every day.
Marshall Roshto