OpenStreetMap logo OpenStreetMap

mcld's Diary

Recent diary entries

Solar panels in the UK - 100,000 spotted!

Posted by mcld on 12 September 2019 in English.

The OpenStreetMap UK community has come together for a 3-month “quarterly project” to find all the solar panels in the UK. And the results so far… wow!

-> We’ve just reached over 100,000 standalone solar PV installations mapped in the UK!

-> Plus we also have almost 600 solar farms mapped, representing almost 5 gigawatts!

To give you an idea of completeness: the UK government believes there are about 1 million solar panels in the UK, and official solar farm listings have about 8 GW. What we’ve mapped so far is way more than I thought we’d manage, so I really deeply want to thank every person who contributed, large or small. We can use these data to pilot CO2-saving initatives - and so can anyone else. Open data for the win!

Here are a couple of simple plots from me, to show where the items are in the UK. (The data I’ve used are from yesterday, which is why my plot says not-quite-100,000 items.) I’ve plotted two different types of item: (1) “standalone” solar panels (i.e. ones that are not inside solar farms); (2) solar farms. You’ll notice the distributions are really different:

(The images aren’t showing up…. you’ll have to view them on my blog where I originally posted this)

Some of the darkest blobs on the map are evidence of focussed effort. I know that Jerry (SK53) has been mapping around Nottingham, Cornwall and other areas, so may be the source of some of these blobs. We’ve shown that with some local effort, and a bit of scanning through imagery, a lot of this can be done.

You’ll notice that many of the solar farms are in the southern part of the UK, at least according to our data. That’s not unexpected!

For more detailed data breakdowns, you can peruse Gregory Williams’ solar mapping analysis site.

We have more time to go until the end of the quarter… and we’ll be able to use the data for sustainable energy projects whenever you contribute - so please do join in!

Mapping larger solar farms in England

Posted by mcld on 29 March 2019 in English.

I’ve had a look at mapping solar farms in England. By “solar farms” I mean the large field-scale things.

A few years ago someone put this very useful List of under construction and operational UK Ground Mounted Solar Farms on the wiki, sourced from the “REPD”.

I’ve been through and checked for every item in that table which is rated as >= 30 MW. About two thirds of them were already there. The rest were easy to map because very visible in DigitalGlobe imagery - most of them were not visible in Bing imagery because the latter is a few years old, and many solar farms are new.

(One of my changesets.)

In some cases I’ve used a single power=generator way, but in most cases they’re a power=plant relation. The tagging is generally like this:

generator:output:electricity 	31.6 MW
name 	Broxted Solar Farm
power 	plant
repd:id 	1592
source:generator:output:electricity 	repd
type 	site

This is in ADDITION to the tagging of solar panel areas using the PV tagging described here

I’m broadly following the approach in the wiki page with the big REPD list. The repd:id is useful to be able to join the dots later.

Spotting solar panels in London

Posted by mcld on 11 March 2019 in English.

Jack had this great idea to find the locations of solar panels and add them to OpenStreetMap. (Why’s that useful? He can explain: Solar PV is the single biggest source of uncertainty in the National Grid’s forecasts.)

I think we can do this :) The OpenStreetMap community have done lots of similar things, such as the humanitarian mapping work we do, collaboratively adding buildings and roads for unmapped developing countries. Also, some people in France seem to have done a great job of mapping their power network (info here in French). But how easy or fast would it be for us to manually search the globe for solar panels?

(You might be thinking “automate it!” Yes, sure - I work with machine learning in my day job - but it’s a difficult task even for machine learning to get to the high accuracy needed. 99% accurate is not accurate enough, because that equates to a massive number of errors at global scale, and no-one’s even claiming 99% accuracy yet for tasks like this. For the time being we definitely need manual mapping or at least manual verification.)

(Oh, or you might be thinking “surely someone officially has this data already?” Well you’d be surprised - some of it is held privately in one database or other, but not with substantial coverage, and certainly almost none of it has good geolocation coordinates, which you need if you’re going to predict which hours the sun shines on each panel. Even official planning application data can be out by kilometres, sometimes.)

Jerry (also known as “SK53” on OSM) has had a look into it in Nottingham - he mapped a few hundred (!) solar panels already. He’s written a great blog article about it.

See full entry