Last week I wrote about the benefits of open data in the transport sector, and how it could lead to more efficient transport. Here’s a good example of the same thing in the energy sector: this week National Grid opened up their 48 hour forecasts for carbon intensity, which combine projected energy demand with the weather forecast.
You can view the next two days in two-hour sections, with the expected carbon intensity for each slot. In some cases there is high demand and little coming in from wind or solar. That means more energy being provided by fossil fuels and high carbon intensity. Other times have lower demand and there’s a good supply of energy from the sun or wind, and so the carbon content of our energy falls.
This data is useful because developers can now use it to create apps or smart appliances that can anticipate energy demand and run accordingly. An electric car could plan when to charge, taking advantage of periods of lower carbon intensity. Fridges could plan the cooling cycle so that they need less power during peak times. Domestic batteries would release stored power at carbon intense times and recharge at times of surplus. With enough smart devices in use, we could even out some of the high points and reduce the need for baseload. This is all part of a connected energy future where energy use is managed for efficiency and even load, and the carbon intensity API is one potential tool in making that a reality.
Those of us with an interest in lower emissions don’t have to wait for those future devices. We can consult carbonintensity.org.uk and choose when to run the washing machine if we’re so inclined. Here’s the advice at the time of writing, courtesy of a widget developed by WWF: unplug charging devices during the 6-8pm slot. The greenest charge time is going to be early morning tomorrow.
There’s only so much one can do with this information right now. I for one will not be setting the alarm to get up and do my laundry in the middle of the night. But it’s not really for likes of you and I in its raw state. With the data available, developers can find uses for it and that’s where we can get involved. Some of those uses may be quite unexpected, and I’ll be keeping an eye out for any interesting solutions that come out of National Grid’s data.