Dynamic electrical pricing demands dynamic price data.

The power industry has begun its long-anticipated shift towards demand-based pricing of electricity. Dominion Power, my electric company here in Virginia, has two basic rates: winter and summer. Although the math is a bit complicated, electricity costs about 50% more in the summer than in the winter, averaging 12¢ per kilowatt hour. (One can also pay for sustainably sourced energy, as I do, and this raises these rates by 1.3¢ per kilowatt hour.) While this price system is very simple, it is also bad, because it fails to respond to consumer demand or the realities of electrical generation.

Here’s an explanation of the problem and the proposed solution: open electrical rate data.

Excess Demand

On a very hot day—say, north of 100°F—everybody wants to keep their house at 72°. This requires a great deal of electricity, which means that Dominion has to generate a great deal of electricity. And that’s fine, because people are paying per kilowatt hour. If they want to pay $1 an hour to keep their house cool, that’s their prerogative. They pay, and Dominion uses the money to run their plants. But this all starts to fall apart when Dominion nears its maximum capacity.

As demand approaches capacity, Dominion is faced with a dilemma. Like most power companies, Dominion probably has a standby boiler in their coal-based power plants. This is not normally fired up, because it’s the oldest, polluting-ist boiler that they have. This boiler falls well below the modern standards of efficiency within state and federal regulations. Turning it on might increase by tenfold the power plant’s emissions of regulated pollutants, and guarantees that they’re going to be paying fines. At 10¢ per kilowatt hour, running their modern boilers is a profitable enterprise, but running the ancient, standby one is a money-losing endeavor.

In order to avoid brown-outs—demand exceeding capacity, resulting in insufficient amounts of power being delivered to customers—Dominion has to start up this nasty old boiler, even though they might only be needed to provide power to a few thousand customers. The incremental cost of serving these few customers is enormous, but necessary to keep the whole enterprise going.

Worse still, imagine if the temperature continues to climb. Demand spikes further. More power is needed than Dominion can generate or buy from other power companies (who are dealing with the same problem). Brown-outs or rolling blackouts are now impossible to avoid. Customers are angry. Dominion is losing money.

Dynamic Pricing Models

Enter dynamic—aka “demand-based”—pricing. There are two ways that dynamic pricing can work.

The first dynamic pricing model is based on a schedule of rates relative to demand. This tells customers how much power costs on low-demand days versus high-demand days, with any number of gradients between the two. And within that daily rate difference, there are price changes throughout the day. A low-demand day might average around 9¢ per kilowatt hour, and a high-demand day might top out at 20, 30, even 50¢ per kilowatt hour. The advantage of this system is that it’s controlled and limited—people know what the possibilities are, and there’s a theoretical cap on how much power can cost. The disadvantage to this system is that there’s no way for customers to know how much collective demand exists. While Dominion understands that a high-capacity day is anything north of (say) 25,000 megawatts, customers have no way of knowing how high that collective demand is. This is an actual system that exists around the nation right now, and that Dominion allows customers to opt into.

The second dynamic pricing model is based on a real-time auction of electrical rates. For this approach to work, you’d tell your appliances how much you’re willing to pay to run them. You’ll pay no more than 35¢ to dry a load of laundry. You’ll pay no more than $2.50/day to keep your house cool, unless your house gets above 78°, in which case you’ll pay up to $5.00/day. Your water heater will keep water at 130°, unless power goes above 15¢ per kilowatt hour, in which case it will drop to 120°. And so on. Then your home power meter aggregates this data, and makes bids for power, bidding against every other customer. This works somewhat like eBay’s automatic bid system, and very much like Google Ads’ pricing model. Of course, this infrastructure does not exist yet, and so this is entirely in the realm of the imaginary. Still, I feel comfortable saying that this system is inevitable.

Returning to the reality of the first model—a published rate schedule—there’s a serious problem with information asymmetry. How is one to know the cost of electricity at any given time, if you don’t know if it’s a low-, medium-, or high-cost day? Dominion’s solution to this is both straightforward and complicated: they’ll e-mail you at 6 PM every day and tell you which of three rate structures that they’ll use the following day. Each rate structure changes over the course of the day, with different prices overnight, in the morning, through the bulk of the day, and in the evening.

But, wait, it gets harder. Dominion also institutes a “demand charge.” Every half hour, they sample how much power that you’re using at that moment. Then your monthly bill has a fee based on the largest amount of power that home was using at one of those sampled moments in the prior 30 days. If you used no power all month, except for one minute in which you used a very large amount of power, you would be billed a corresponding large amount, despite your near-zero average.

For customers, Dominion’s approach is dizzying. It requires that people keep track of electrical rates on a day-to-day and hour-to-hour basis, peak home power usage at all times, and provides nothing that would support the growing industry of home automation and energy saving devices, which could manage electrical use automatically. The popular Nest thermostat can be automatically reprogrammed via the internet. Apple recently announced an entire platform of home automation tools, controllable and configurable via iPhone, iPad, or desktop computer. Philips makes a light bulb kit that permits each bulb to be controlled remotely, the brightness and color of the bulbs configurable individually. There’s a whole ecosystem of hardware, software, and data to allow one’s home’s energy use to be adjusted in response to external factors. But what they can’t do is read Dominion’s e-mails at 6 PM every night. That’s an unbridgeable air gap, a failure on the part of Dominion that is perhaps mystifying or perhaps rational, depending on one’s level of cynicism.

Open Electrical Rate Data

There’s a simple solution to this: open electrical rate data. In addition to sending out an e-mail at 6 PM every day, Dominion could maintain a file on their server that provides machine-readable data about current and near-future power rates. It might look like this:

Right now, the closest that they get is a retrospective page, which has allotted space for the next day’s price (“Classification for tomorrow:”), but the page text ends with the colon—I’m yet to see that classification provided. [Hours after I published this, Dominion finally wrote something in that space, I assume prompted by the 90°F forecast.]

If this data was provided, it would be trivial to use it to enable home automation and energy management tools to schedule and control energy-intensive home services and appliances.

And, in fact, that’s a feature that Nest supports. The thermostat will dynamically adjust the temperature of a home during the highest-priced periods, generally very hot summer afternoons and very cold winter nights. But because precious few power companies provide the necessary data to support this feature, it’s not useful to most Nest customers. Nest doesn’t provide a comprehensive list of participating power companies, and after searching through their press releases and trying out a handful of ZIP codes from across the country in their form, I have to conclude it’s because there are very few participating power companies.

Publishing open electrical rate data is not difficult. If they can send out an e-mail, they can certainly update a JSON file. For a competent developer, it would be an afternoon project. A company that is capable of managing an entire electrical grid and the entire usage tracking and billing system that accompanies it is certainly capable of a tiny project like this.

I’ll warrant that Nest—which is owned by Google—is in a good position to establish a standard JSON schema for power companies to use. Some power companies would probably welcome being told what schema to use, giving them one fewer thing to worry about. Right now, it appears that Nest is basically taking any data that they can get. (It wouldn’t shock me to find out what they’re intercepting night-before e-mail alerts and using those to update thermostats with rate data.) Power companies are going to catch on to the enormous importance of rate data, and Nest has the first-mover advantage. I hope that Nest puts together an uncomplicated schema, advertises it on a developer page, encourages existing and new partners to publish in that schema, and eventually requires that participating power companies comply with their schema, assuming that they end up in a position where they can make such demands.

Open electrical rate data will provide real savings to consumers and utilities alike. It’s a necessary and inevitable development in power distribution and home automation. I hope that power companies and Nest take the simple steps necessary to usher in this era of open energy data, and soon.