Is Flexibility the new Efficiency?
10 June 2017
On 7 June 2017 around lunch time the UK generated the majority of its electricity from non-fossil fuels. That was the first time, the first time ever. It also was the time when wholesale prices for electricity plummeted to a tenth of their normal level.
It's a sign of things to come. Renewables are falling in cost so rapidly that cost is no longer their problem - it's becoming our problem. Low costs that is. Once built their electricity at time of generation is practically free (i.e. one doesn't save a penny not to produce it - very different from plants with fuel costs). When the sun shone and the wind blew on 7 June, all that renewable electricity displaced more expensive (yes, more!) fossil fuel electricity. Wholesale prices head towards zero temporarily.
What does that mean for us, the 'just about managing' electricity users? Sadly, as things stand, nothing at all. We cannot get our hands on that super cheap electricity at the time, nor are we likely to see it in lower bills over the year. There are two reasons for that: in order to benefit from temporarily low prices one would need to know how much you were using at that time. With electricity meters being read randomly every six months that is impossible to tell. Hence, the need for smart meters, which could in theory give us a different price every 30 minutes.
Before you jump for the opportunity to get your hands on these low cost periods, there is inevitably a flip side. The reason we won't necessarily see lower bills despite lower cost renewables is that there are of course times when they are not available. And those times can become much more expensive. You could blame coal and gas power stations for the highest prices, but that would be missing the point. They are faced with a tough prospect: all the cheap renewables are eating away at their market. Fewer and fewer hours remain when coal and gas plants can operate. With fixed costs stubbornly, well, fixed, the price for the remaining electricity they produce goes up.
So how do we get the cost down? Easy: if we all continuously avoid the most expensive periods, some of those old power stations can enter their well deserved retirement, overall prices fall, as do emissions. Even better, at times with lots of sun and wind we can even use more electricity. It is no longer about efficiency (using less), but flexibility (using wisely).
Is that a realistic prospect? Would you reschedule when your appliances run? Are you even able to? Smart technologies might help, but much of our lives don't give us much room for movement. The University of Oxford tries to understand the time pressures in our lives and how they shape our energy use. Take part and you could help bring down the energy cost for all (and with a bit of luck win a year free electricity for yourself - that really brings down the cost).
Why is so little know about electricity use?
Authoritative looking pie charts like this one
give the impression that we know who is using how much, for what and when. In fact these figures are rough estimates of averages. They are often based on assumptions and a few measurements in small studies.
These studies are very limited in their ability to
- capture the timing of electricity use – be that the time of day or season of the year,
- give some sense of the diversity of users – some use a lot, some very little and it depends a lot on circumstances,
- highlight the scope for changing electricity use – which uses are essential, which ones would go unnoticed if we shifted them a bit?
There are two main reasons why these details are poorly understood:
- We didn’t really need to know (until now)
- It’s not that easy to find out
1) We didn’t need to know
Fossil fuel power stations are very good at responding to our electricity demand. When you switch a light on, somewhere a power station will increase its output by a small amount. This keeps supply and demand in balance – second by second.
So long as the system operator can roughly estimate how much electricity we require collectively over the next few hours, this approach works well. No need to know what this electricity is used for.
However, as wind and solar generate more of our electricity, it becomes harder for supply to follow demand at every instance. One hope of system operators is that demand itself could become flexible. For that to happen it does become interesting to understand what ‘causes’ all that electricity use, so that we can find effective ways to avoid or shift it.
2) It’s difficult
The second reason why we know little about electricity uses in households is that it isn’t that easy to find out. A 6 monthly meter reading certainly doesn’t tell us much.
Various approaches have been applied.
Appliance stock models: One can try to estimate how many appliances we have in our homes from retail sales figures. However, that still leaves us guessing when and how much we use them.
Household instrumentation: A more direct way to find out is to measure appliances directly in the homes. That means every light, every appliance from the vacuum cleaner to the cooker must be ‘wired up’ and measured. This process is very intrusive for the people in the household and it is also quite expensive. So expensive that no more than 50 households can be observed in this way – nowhere near enough for statistically robust research.
Demand disaggregation: A novel way to reduce instrumentation cost is to take a high resolution reading at the household’s main meter and try to recognise which appliances are in operation based on their characteristic profile. Fridges, for example, have a typical on-off pattern, washing machines can be identified by their spin cycle and even smaller good give away clues when observed closely.
While these approaches are getting better at finding out what the appliances are doing, they still don’t tell us much about what we are doing. The television might be on – but is anyone watching it? All the lights are on, but is anyone actually at home?
If it is flexibility we are after, then these differences matter. This study will take a very simple approach to find out: we ask people what they do. Here is how…
The shape of UK electricity use
On a typical winter day the 'load curve' looks something like this:
Each morning it ramps up (left slope) and peaks in late afternoon (top hump). The ramps are a challenge, because power stations are big and can't respond very fast to changes in load. And during the peak pretty much all UK power stations are hard at work. If anything goes wrong, such as a power station having a fault, the system can be under severe stress.
So we have options: build more conventional power stations (quite expensive and environmentally problematic), build storage (also expensive), or try to reduce that hump. How much of the electricity in that hump might we be able to shift to a less problematic time?
This is where we have a knowledge gap, because we don't really how much of the hump is used for what and by whom. Are there people who do a lot of cooking, washing or cleaning at this time - and might they be willing to do it sooner or later instead? How much might that change the hump? This projects is about to find out.
To do so, we will combine electricity data with 'time-use' data. Time-use researchers know very well what we do. They have collected activity information for decades. From such data we can build up a national picture like this one:
Find out how METER research will combine these insights
to shine a light on what we do with electricity and how you can take part