Grid flex rhymes with derivatives trading: an observation

[DamonHD]

https://www.academia.edu/2998-3665/3/3/10.20935/AcadEnergy8514

 

Introduction: To eliminate the ~15% of UK greenhouse gas emissions due to home heating most will move to heat pumps by 2050. But electrifying heating will roughly double peak demand on the grid while green intermittent renewables such as wind and solar make available generation less predictable. Most of us will need to learn to flex our home space heat and hot water and other electricity demand else we will pay a high premium, but we do not all have to flex in the same ways at the same times to support the greening grid.

Materials and methods: This study synthesises existing literature and first-hand observations from investment banking derivatives and the energy system, along with primary data from one UK home enumerating a number of viable techniques.

 

Results: Static and dynamic demand-side flexibility responses, automated and manual, have visibly moved the case study home’s load profile away from that of a typical Great Britain (GB) household on winter weekdays when national demand is highest.

 

Conclusions: A portfolio approach with a mixture of different grid flexibility responses across the housing stock, including those driven by Time-of-Use tariffs, can be a first-class contribution to Net Zero.

 

 

[MikeSharp01]

Very interesting, we are all going to have to get smarter in one dimension or another to manage this are we not?

[JohnMo]

But will the general population be interested or bother.

 

Example - I am currently on a ToU tariff for import and export and moving our heating to be on during low tariff (low demand) periods as much as possible and have batteries to move the electric usage during cold spells back to the low demand periods. But it takes effort and not all houses are suitable - as they leak heat like a seize.

 

Daughter is just on bog standard rate tariff and is very unlikely to move - too much effort.

 

But I find it interesting watching Agile export rates and how periods of excess grid energy pay almost negative rates for export, while other times of short supply they will pay more than import rates. Then you have Axle that pay you a £1 per kWh again when power isn't readily available.

 

It's worth the effort - compared to last September, our energy bill is on track to 80% lower this year.

 

Just need more people to understand the financial benefits and the environment benefits also come as a direct consequence of the changes

 

 

[SteamyTea]

How will the grid react if individual homes are responding to frequency/voltage variation.

A million homes can increase, or decrease, consumption in a few minutes, even a small generator takes several minutes to react, a large one a few hours.

Can you model a central control, using historical data, against a million independent agents 'doing their own thing'?

Will there to too many limits on independent systems to make it worth while?

[DamonHD]

New GB grid frequency response services, eg from batteries, are required to respond in a second or so:

 

https://www.neso.energy/industry-information/balancing-services/frequency-response-services

 

Linear frequency/power responses and a dead-band help prevent them making things worse.

 

Millions of devices should avoid deliberately or accidentally synchronising to cause 'herding' effects: my own response mechanisms generally add at least some seconds' randomness before going on load or coming off a response to low frequency.  The 10-minute randomisation for EV charging is another anti-herding design.

Edited 2 hours ago by DamonHD

[DamonHD]

2 hours ago, MikeSharp01 said:

Very interesting, we are all going to have to get smarter in one dimension or another to manage this are we not?

 

Maybe.  But things as simple as adjusting heating/water times and picking a suitable tariff is at the easy end for example.

[DamonHD]

2 hours ago, JohnMo said:

Just need more people to understand the financial benefits and the environment benefits also come as a direct consequence of the changes

 

I suspect that non-ToU tariffs may become much more expensive, so those who pay no attention at all will pay a heavy premium; those who pay more attention will save (or earn) significantly.

[MikeSharp01]

3 minutes ago, DamonHD said:

Maybe.  But things as simple as adjusting heating/water times and picking a suitable tariff is at the easy end for example.

 

Naturally -  but you have spun out a whole other idea here - real time trading of energy consumption. I can imagine an AI agent getting control of a smart enough home to really drive down costs and consumption.

 

 

2 hours ago, JohnMo said:

But it takes effort and not all houses are suitable - as they leak heat like a seize.

Yes but if you achieve 80% cut in cost and use AI to control it why would you not.

 

[DamonHD]

Just in case anyone likes those "making of" backstories...

 

https://www.earth.org.uk/pint-poster-paper-slice-and-dice-decarb.html

[JohnMo]

1 hour ago, MikeSharp01 said:

Yes but if you achieve 80% cut in cost and use AI to control it why would you not.

But people still think ASHP cost more to run than an ASHP and solar is ugly and would never have them.

[SteamyTea]

Getting some data from here:

https://data.nordpoolgroup.com/auction/gb-half-hour/prices?deliveryDate=2026-09-19&currency=GBP&aggregation=DeliveryPeriod&deliveryAreas=UK

 

Plotting Price and Volume, you get this.

Not sure that increasing price has much to do with volume.

(a lot more data point would be needed, but had a busy day and I am tired.  The peak price was between 18:00 and 20:00, but the biggest draw was 07:00 to 08:00 and the price was negative)

 

 

 

Delivery Period	MWH	£
23:00 - 00:00	198.5	46.21
00:00 - 01:00	166.3	34.42
01:00 - 02:00	112.6	15.88
02:00 - 03:00	123.9	4
03:00 - 04:00	229.9	-1
04:00 - 05:00	323.1	-1.64
05:00 - 06:00	397.9	-1.64
06:00 - 07:00	377	-1.63
07:00 - 08:00	464.6	-1.66
08:00 - 09:00	274.5	3.3
09:00 - 10:00	112.3	4.43
10:00 - 11:00	154.6	3.1
11:00 - 12:00	210	-1.46
12:00 - 13:00	188.2	-1.24
13:00 - 14:00	173.7	-1.6
14:00 - 15:00	177.6	-0.09
15:00 - 16:00	86.6	4.32
16:00 - 17:00	124.1	9.35
17:00 - 18:00	349.7	65.1
18:00 - 19:00	152	106.32
19:00 - 20:00	156.4	106.8
20:00 - 21:00	191.2	96.82
21:00 - 22:00	151.9	86.04
22:00 - 23:00	109.2	62.56