Posts Tagged ‘currentcost’

How much did I spend on electricity to do that?

Friday, November 27th, 2009

Selecting a chunk of a graphTime for number 73 in my never-ending list of ever-so-slightly-different things to try with a graph of home energy usage data

🙂

This time… working out the electricity used (and the cost) of doing… well, something in particular.

We already have live graphs (Switch something on and watch the graph shoot up. Switch it off and watch the line drop.)

And we’ve already got graphs with hourly, daily, or monthly totals.

But if I boil a kettle, how do I know how much that cost?

The live graph shows you the shape of the usage curve for a particular appliance.

What I wanted was to be able to start the live graph running, switch something on, then after it’s finished, go back to the live graph, see the bump in the graph for when I did that, and measure the area under it – giving me my total energy usage for that time.

A quick bit of Python-tinkering later, and here we go

Click-and-drag to highlight a span of the graph, and the Python script calculates the area (more-or-less) under that part of the curve, using this to calculate how much energy I used during this time.

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Where did your electricity come from?

Monday, August 17th, 2009

Where did my electricity come from?It’s been a while since I posted about CurrentCost stuff, so time to share another little idea.

Last night I made a start on adding a new graph type to my CurrentCost application.

Instead of only displaying how much electricity you’ve used, the new graph displays the split of how that electricity was generated.

Realtime figures for the “energy mix” of ratios of different generation methods used in the UK National Grid are available in an XML feed that updates every five minutes.

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HomeCamp 2

Wednesday, May 20th, 2009

Saturday 25th April saw the return of HomeCamp. HomeCamp started last year as the brainchild of Chris Dalby, aiming to bring together a growing community of people interested in “green” hacking and technologies.

I’ve had this post sat in draft for weeks now, meaning to come back and turn them into proper notes. As it’s been a few weeks now and I still haven’t, I thought I might as well post my rough notes as I took them on the day. Apologies that they’re a little sketchy!

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Pretty CurrentCost graphing from Pachube

Tuesday, April 28th, 2009

Last Saturday was the second HomeCamp. This week has been very busy at work, so I’ve not had the chance to pull together a proper post about it yet, but in the meantime I thought I’d share a little Pachube tip that Usman demonstrated at the event.

I’ve been putting the live readings from my CurrentCost meter into Pachube as an input feed for several months now, but not really had much use for it, other than as an easy way to check my CurrentCost data from my mobile.

Usman showed us an app that lets you get a neat Google chart visualisation of a Pachube feed in just a few clicks:

It’s very simple – go to apps.pachube.com/google_viz, give it the ID of your pachube feed, and it generates the short snippet of code necessary to create the Google chart.

It takes no time at all, and really shows the power of being able to easily pipe together different stuff through pachube.

BathCamp evenings

Wednesday, March 18th, 2009

bathcamp T-shirt

In September last year, a barcamp was held in Bath. It was called, somewhat predictably but not unreasonably, “bathcamp“. 🙂

I blogged about it at the time, but in short it was a fascinating weekend that brought together a great group of people.

But it didn’t end there.

There will be another bathcamp event, but the organiser Mike Ellis had the very neat idea to keep the momentum going in between the full barcamp weekends with a series of monthly evening meetups.

The first Wednesday of every month, BathCamp becomes an evening event at Revolution in Bath. It works really well, keeping the sense of community going in between the full barcamps. Many turn up early, in time to have a drink and something to eat in the bar downstairs. You get a group of people all sat together, but it’s very welcoming and friendly. You can sit next to anyone there, and get involved the conversation – not always the case with every geeky meetup I go to.

At about 8pm-ish, everyone goes upstairs for an informal presentation on some tech topic of interest. Then there is a break where everyone gets themselves a drink, and talk and bounce around ideas about the presentation.

Then another (generally somewhat related) presentation from a second speaker, and another chance to talk about the topic with everyone else there. These bits make a difference – sometimes these events can drift into “turn up, listen to talk, go home”. But so far, the Bathcamp meetups have been a long way from that.

The talks so far…

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Responding to the state of the National Grid

Sunday, February 15th, 2009

Okay, I know I said I’d stop banging on about CurrentCost stuff… sorry. My next post will be about something different. Honest! 😉

But with talk about Home Camp 2009 starting to pick up, it seems like a good time to remember one of the interesting factoids I picked up at Home Camp last year.

As I wrote at the time:

…the frequency of the electricity you receive from the National Grid is proportional to the ratio of supply vs demand for electricity usage on a national level…

There was a lot of discussion about how this information could be used to make a difference.

This is discussed in more depth at dynamicdemand, but the sort of thing we talked about was how you could make a significant difference without reducing your total electricity usage at all, but by shifting your usage to times when national supply is greater than the demand, and so when the energy is cheaper and more efficient to produce.

As I wrote at the time, it might be interesting to see what this looks like plotted against your own personal electricity usage.

Demonstrating my lightning quick l33t development skills, only ten weeks later, I got round to trying it out. 🙂

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Getting data from the CurrentCost CC128

Saturday, February 7th, 2009

I really need to stop blogging about CurrentCost stuff, this is starting to look like an obsession 🙂

But before I do that, I thought I’d share my experiences in writing a new CurrentCost parser.

What is this all about?
On the off-chance that anyone following me hasn’t already heard about CurrentCost a million times already, CurrentCost meters are domestic electricity monitors that tell you how much electricity your household is using. And they have a connection underneath that lets you grab the data from them.

As well as getting your current electricity usage, you can also get historical usage totals out of the serial port, which I’ve used in a variety of ways, such as in my Python CurrentCost software.

CurrentCost have now brought out a new model of their monitor – the CC128. The data format is different to the current models, so I wanted to try and write a new parser that could handle both the existing model and the new CC128 data.

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Another CurrentCost app update

Sunday, January 4th, 2009

The tabbed interface in my CurrentCost app continues to serve me well. It means I can keep adding new pages to try out new things to display and compare, without spending any time rethinking the interface to make room for another graph.

I added another this morning. When you sync the app with the web, it downloads (anonymised) daily power usage values for every registered user, and plots them on a single scatter graph.

I wanted to do this for every stored daily power usage value, but it was unwieldy. I’ve settled for having the web service calculate average daily power usage for each user, and plotting them instead.

plotting everyone's CurrentCost readings on a single scatter graphEach cross on the graph for a day represents a different user, which is neat – a nice way of seeing trends. By plotting my own usage in a different colour, I can see where I am in the distribution.

If you’ve not tried my app yet, please do consider it. The more people I can get submitting data to the web service, the more interesting these graphs become!