This article was published in Scientific American’s former blog network and reflects the views of the author, not necessarily those of Scientific American
In one of the best quips I've ever heard at a scientific conference, cosmologist Max Tegmark complained about a lecturer's vagueness and pleaded for some quantitative predictions: "numbers—you know, the kind with decimals in them." Like Tegmark, I love data. Concrete information beats hand-waving speculation any day. So it's awfully fun to use a home energy monitor to track your household electric power use in real time. Practical, too. Knowing how much you spend is always the first step in figuring out how to save. Studies show that people who have home energy monitors find ways to cut their electric bills.
Over the summer, data-lovers suffered a blow when Google pulled the plug on its Powermeter website, which provided a convenient way to track your home's electricity use. But shortly after I bemoaned its demise, I learned about several other sites that are in some ways even better. They not only display your power consumption but also analyze it for patterns that could help you save money.
To collect the data, I have a unit called The Energy Detective, which consists of a pair of sensors that you clamp around the main power cables in your circuit breaker panel. Other systems, such as those by Blue Line and WattVision, attach to your utility electric meter. All take power readings and keep a running tally you can view through a web interface or mobile app. Lots of other devices are other there—energy blogger Chris Kaiser keeps a comprehensive list—but not all can upload the data to external analysis websites.
On supporting science journalism
If you're enjoying this article, consider supporting our award-winning journalism by subscribing. By purchasing a subscription you are helping to ensure the future of impactful stories about the discoveries and ideas shaping our world today.
Those sites crunch the data and give you a breakdown of where the juice went. They rely on the fact that each appliance has a telltale pattern of power demand. A fridge, for example, regularly cycles on and off—you can easily see it on a graph of your total household power consumption. In principle, the analysis algorithms could go a-huntin' for power hogs such as broken appliances and family members who crank up the a/c when you turn your back.
Unfortunately the TED monitor can work with only one external website at a time. PlotWatt had the cleanest interface, so I decided to give it a go first. You type in some general information about your house, such as how many of which types of electric appliances you have, so the algorithm knows what to look for. The site said it would take a week before it had enough data to perform an analysis. A week went by, then two, then three. Emails to tech support went unanswered and, out of frustration, I tracked down the email addresses of the site developers, who apologized and said they'd been swamped by people migrating from Powermeter and another soon-to-be-defunct site, Microsoft Hohm. After a month, I finally got some results.
The level of detail was somewhat disappointing—I was hoping for a finer-grained breakdown, revealing patterns I wouldn't have expected. Still, PlotWatt correctly inferred that window a/c units were our biggest energy sink. On the chart, you can see demand ramp up because of the midsummer heat wave. Our solar panels covered only about half my total demand over this period. Previous summers haven't been so extreme and we usually don't even put in the a/c until August. You can also see flatlines where the TED stopped sending data and had to be rebooted.
After putting PlotWatt through its paces, I reconfigured my TED to upload data to another site, EnerSave, and began to wait again. This time, it took two full months—I got my first results only two days ago. And they disagreed with PlotWatt's. For the one load that should be fairly constant—the fridge—they differed by a factor of three.
One reason may be that, unlike PlotWatt, EnerSave does its analysis on net consumption—it doesn't add in the solar power generation to get our total consumption. When I signed up, I asked the developers about this and they claimed that net consumption would be enough to detect patterns. Later, though, they backtracked. They said they are still tinkering with their algorithm, so I'll let it run a bit longer before I switch to a third service, MyEragy, and try it out.
The EnerSave user interface has the distinct advantage of showing you exactly when the algorithm thinks certain appliances cycled on and off. This is revealing not so much of our power habits, but of the limitations of the algorithm. For instance, the graph shows that on August 27th, the room a/c ran almost continuously. That makes sense: we were starting to get water in our basement from Hurricane Irene and the dehumidifier (which registers as a/c) ran all the time. But the graph also suggests that the dehumidifier cycled on and off over the subsequent week, whereas in actuality it ran almost continuously until our basement dried out.
Clearly, these are works in progress. A more reliable way to get detailed data about your power consumption is to attach a hardware sensor to each appliance. Some energy monitors, such as EcoDog and eMonitor, do just that. But they are much more expensive and I personally can't justify the extra cost. Love of data has its limits.
Screen shots by George Musser