November 13, 2014
by Christopher Gutteridge
UPDATED Friday 14th. See end of post for update about the plans.
Friday sees the 3rd annual University Blackout event where everybody is encouraged to turn off their electrical equipment so we can see how much energy is save. Later in the evening, a team of 250 volunteers scamper around offices turning off remaining monitors and computers unless they have a pre-approved excemption certificate taped to them.
Obviously the savings this makes are only a drop in the ocean, but the headline figure in the infographic is 6%. I was interested in how they got that number, as last year I ran a building-by-building analysis of energy use, based on the open data provided by their system for each main building. eg. http://data.southampton.ac.uk/building/59.html?energy
From the horse’s mouth
(..or do I mean horse’s meter?)
I was invited to go and see how the system all works, and wheree the data comes from. It’s a small team with many responsibilities and bits of the system are more aged than other, so they can’t do all things for all people. They are monitoring well over 100 buildings over many sites.
To give the value for a building they use a virtual meter which is a function on top of one or more real world meters. The function can add the values of several meters, and sometimes apply a fiddle factor for known errors. Metering is not a simple task at these scales and the sum of all the meters never quite adds up. Some of the issues include a misinstallation. This is rare. Suspiciously low readings set off ther analysist’s spidey-sense and physical investigation led to the issue being found and corrected.
There’s more subtle cases though. We apparently have some meters which measure differently, depending on warmth, and we have meters which measure hot water flow which get slowly clogged and the measurements alter until they are cleaned, but that involves shutting stuff down and can’t be done often. It’s not all meters that play up, but the ones that do need to be considered when drawing conclusions from data.
I should stress that these are our internal meters which we use to monitor our systems, not the meters that decide how much we pay.This year the plan for measuring the impact of the blackout event is to focus on the campus figure rather than by building. A keen reporter at SotonTab, the unofficial student news site, got someone to total up energy usage all the buildings over last year’s Blackout, but given the variation of meter performance it’s hard to trust this data. The margin of error is higher than the number we’re looking for. This year the provisional plan for the official figure is to use the main power consumption value for each campus rather than using sets of individual buildings.
A molehill, but a molehill on a mountain
One of the big concerns with the project, that I share with some other malcontents, is that it is a feel-good exercise which does nothing to address the real issues of energy reduction. What I was unaware of is all the other work already done and being done to waste less resources.
The really big one I was aware of but never really thought about, which is the Combined Heat & Power system on Highfield Campus. What this does is uses gas to generate both electricity and heat for the campus, wasting less energy (and causing less carbom emissions) than getting electricity from the grid. We hope to soon start publishing the summary data, but the headline figure is about half-a-million quid a year saved, or to put it another way. Imagine several hundred 1000 Watt heaters all running full blast all day every day, year in, year out, and for no good reason. That’s about the amount of energy the CHP system is saving. It ain’t the most sexy thing about our university, but it’s something we can all feel a bit of pride in.
Another part of their job is to study the data and spot and investigate changes in the way each building uses energy and see if there are any things to be done about them.In the context of all of these big things already being done, it starts to make more sense why they are now working on higher-effort, lower reward tasks such as encouraging people to turn off unused stuff– they’ve already done much of the easier savings.
- More information on university carbon management projects
- Lots of data (sheets) about building energy efficiency
But what’s actually worth turning off?
Many years ago I used a little gadget to find out how much power all my electronic posessions drew when on, and when on standby still turned-on-at-the-plug. It helpped me understand where it was most useful to put effort into powering off and unpluging my stuff when not in use.
There were two main surprises…
First of all, my phone charger, when the phone was not attached, used no mesurable amount of power, so I stopped bothering turning them off.
The other surprise was my data projector. It used 200W when projecting but that’s not that surprising, I knew it was a high-energy-use item. What shocked me was that it used 30W when on standby mode doing nothing at all. As a result I always made sure it got turned off at the mains.
Obviously your-milage-may-vary, but the university buys many standard items which are all very similar like computers, monitors, fans, etc. What we could start doing is checking their power use and standby-power-use, and label all the units of that exact type we deploy in office and lab space so that staff can make an informed as to where there’s value in bothering to turn things off.
But why isn’t all the data open?
There’s several reasons to this.
One is that the raw meter data has many caveats to interpretation, and I’ll agree that it’s hard to get people to read the tasting notes going along with open data. One idea I’ve had is to make the “citation URL” the document describing the data, so if you do anything with the data and “must attribute” the data creator, that attribution must be to the document warning of the known issues with the data.
Oh, and some of the meters log an error as “0” (zero) rather than NULL, so that’s not ideal for statistical analysis. This is what you end up having to deal with in pragmatic real-world data.
The other reason it’s hard to get at the raw data is that the only way to get it is via the system which collates it and that is 1996, the era of Spice Girls and Buffy the Vampire Slayer. it might be just a bit older than some of our current freshers.
So obvisously it’s very slow and klunky and as usual the project to replace it is taking longer than hoped.
Why don’t we ask the experts
I asked them why they didn’t make it available and they said (to my embarrassment) that they do, you just need to ask nicely and they’ll give a password to any member of staff or student. They can be reached at email@example.com but remember they are a small team with lots of work, so they can’t just drop everything to help you get started.
Considering the number of experts in data analysis and interpretation we must have on staff and amongst the phd students and even undergrads, I’m hoping there’ll be a few who could help them lift new knowledge out of this data in ways that really can help us make real strides towards the goal of 20% reduction.
We don’t have a very good track record of using the expertise of our research staff to actually feed back into the way we run the university. This is all our fault, but if you think you might be able to add some insight to this (warts and all) data, please do get in touch with the metering team, they’d love to hear from you.
What ideas do you have for using data to save energy?
Update from the Blackout Team on Data Method Analysis
Neil Smith, the person who leads university sustainability projects has sent us this info:
1. Scope: Highfield, Avenue, WSA and Boldrewood (Block B and Annex)
2. Data sources:
- Information on the number of Pcs, monitors and other electrical equipment will be recorded on the night.
- University Automatic Monitoring Recording (AMR) system (for building half hourly electricity data). Note: not available for Boldrewood buildings. Note: the AMR relies on a network of meters and data loggers to record and transmit the data to the central database, data is also supplied daily from the University’s fiscal meter by the University’s Meter Operator Aggregator. In Blackout 2013, the system for a large area of the Highfield campus failed and this made it extremely difficult to calculate the electricity use over the weekend.
- Audit data – the number of Pcs left switched on in a building will be published and compared to the values for 2012 and 2013 (where the data exists)
- Highfield: the initial analysis will be for six high level meters. Note as a result of using these six meters, the data will be ‘noisy’.
- Avenue: one campus meter will be used for the data analysis
- WSA: four meters will be used for the data analysis
- Boldrewood: Validated data is not available for the campus and so only the number of Pcs left switched on will be used to assess the impact of Blackout
- Calculation: The average electricity consumption over the four October 2014 weekends will be compared with the electricity consumption over the Blackout weekend (measured from 1600 on Friday to 10 on Monday to capture when people start to leave and return to work. This data will only be published once checked, validated and signed off. This may take a few weeks.
- Results will be posted on Sussed.
- A spread sheet showing the electricity data analysis will be made available on request
- Raw electricity data is available through the AMR and you can request access to the system by emailing details of the building(s) you are interested in to firstname.lastname@example.org.
- Electricity data is also available through the Open Data site
Thanks very much to the Blackout team for this update.