Arneman says that most of us assume that the things we see around us are the things that cost us. “People ask me, ‘How much energy does my blender use?’ ‘How much does my microwave use? If I did just a little less microwaving, would I save money?’
“The answer is that your microwave is on 30 seconds to two minutes a day, and it really isn’t a significant contributor; it’s really almost invisible in the span of the energy usage in your day.”
Similarly, businesses are in the dark about energy misuse. The actual culprits are lurking out of view. PlotWatt nabs them.
Each with its own ‘wattprint’
Back when PlotWatt founder Luke Fishback worked at Lockheed Martin (yes, he was a rocket scientist), he began questioning why his energy bill was so high. He took what Arneman describes as a “high-tech/low-tech approach” to his investigation.
Fishback set up a digital camera to photograph his energy meter every minute or so, and entered the data into spreadsheets. His friend John Cunningham – at the time completing a PhD in machine learning at Stanford and now PlotWatt’s chief scientist – then wrote an algorithm for “energy disaggregation,” thereby planting the seed from which PlotWatt sprung.
Energy disaggregation begins with the premise that each appliance uses energy in a unique way, each with its own “wattprint.” PlotWatt's algorithms sleuth out these wattprints to determine which appliances are the real energy-consumption culprits.
“We tend to think our lights are using a lot of energy,” Arneman says. “But now that many people are switching to compact fluorescents and LEDs, lighting becomes less and less an energy consumer. But that DVR the cable company gave you is actually consuming quite a bit of energy.”
Heat pumps, septic pumps – these too are common wasters.
PlotWatt also tracks always-on energy. “Sometimes people have very high always-on energy use and we can target shutting those items off and see the results,” Arneman says. “The savings really add up.”
Arneman joined PlotWatt in 2011, bringing JMP with him. A dedicated JMP user in his previous work at the University of North Carolina-Chapel Hill, Arneman had helped the university save millions of dollars in energy costs. He came to appreciate the ability of JMP to easily gather, clean and organize large quantities of data from disparate sources, enabling him to ask the right questions of that data and get reliable answers.
At PlotWatt, Arneman uses JMP in his work with homeowners, but it’s with restaurants that he’s really able to demonstrate the value of statistical discovery.
Fast-food restaurants consume up to five times the energy of the average commercial business, and utility bills represent a significant portion of their operating costs. Even so, electricity consumption and associated costs have been “largely invisible to them,” Arneman says. “The energy bill comes in the mail, it goes straight to the main office, and the store manager knows nothing about it. The owner may not even see it except in the profit-and-loss statement as a group aggregate.”
PlotWatt helps reduce energy bills by providing information that store managers can translate into waste-cutting action. They might adjust appliance start-up and shutdown schedules or air conditioner settings. They might reset timers for seasonal changes, so that outdoor lights don’t come on two hours before (or two hours after) sunset. By detecting failing and broken equipment, PlotWatt spurs restaurant personnel to take corrective action sooner.