FAQ: Fundamentals model

• How have we determined the demand forecast? E.g. in terms of future weather scenarios, electrification.
• How do you deal with price cannibalization for storage (and interconnectors)?
• How do you model scarcity pricing?
• How do you deal with negative pricing and CfD payments?
• Can the model deal with curtailment?
• Is there a volume limit to the Balancing Mechanism? If so, how do you set that?
• How did we arrive at our carbon derating factors for gas in the CM?
• How do you know that the commercial model of storage, and other generator types, is viable?
• Do you model carbon?

How have we determined the demand forecast? E.g. in terms of future weather scenarios, electrification.

As inputs, we take the annual peak and minimum demand from the 2023 FES, as well as overall TWh demand. We then split out the anticipated demand from heat pumps and residential charging of electric vehicles.

For the non-EV and heat pump demand, we use historic demand patterns to forecast future demand based on the FES input data.

For EV demand, check out this page. For heat pumps, the detail is here.

We then dispatch EVs against prices within the model and add the granular shape of demand from both EVs and heat pumps back to in to get the national demand, capturing the shifting shape as the electrification of heat and transport grows.

We also put demand side response in the capacity stack at various prices which effectively shifts the demand shape according to price.

How do you deal with price cannibalization for storage (and interconnectors)?

Storage charges up when power is cheap, and discharges when it's expensive.

When you have a lot of storage on the system, it might discharge into the same periods, which changes the supply stack. With the addition of storage, there is suddenly a surplus of generation, and as a result, the price crashes. What used to be an expensive period is now a cheap one (and on the charging side, a more expensive one, though to a lesser extent, as charging is typically more spread out).

This means the opportunity for storage is lost - and the storage makes no (or much less) money.

In reality, high prices would get damped or suppressed as 'peaks' spread into neighboring periods.

In our storage model, we limit the amount of the storage fleet that can dispatch into an individual half-hour period. More information on this here. This acts to soften the price cannibalization.

How do you model scarcity pricing?

Demand side response (DSR) is priced at £250/MWh, £500/MWh, and £1500/MWh. It sits near the top of the generation stack, with loss of load pricing at £6,000/MWh above it.

When there is a shortage of generation capacity (usually driven by low wind), a high price results as demand and generation intersect in this high-price region.

How do you deal with negative pricing and CfD payments?

Depending on the year the CfD has been awarded, payments stop after a certain number of consecutive hours of negative pricing.

Our CfD fleet is split into the early auctions (AR1) and later auctions. The AR1 fleet is priced at -£100/MWh - effectively, it never turns off. The later auctions are priced at £0/MWh.

You might expect, after many hours of negative pricing (above the cap of the auction round), assets turn off as they'd have to pay to generate.

We don't consider the previous half-hour's price when dispatching the subsequent half-hour. This means this is not dealt with in our model. We may therefore have more negative pricing than you might expect - as if these assets were to turn off, there would be less generation on the system (and the price would return to £0 or above).

However, there is uncertainty around how you'd turn off GW of wind or solar with a few hours notice and no major operational cost.

Can the model deal with curtailment?

If you're looking for detail on curtailment for prospective battery sites, see here.

Here, when we discuss curtailment, we mean the curtailment of renewable energy at times of excess generation, or in response to limited line ratings across the network to physically transport power.

The model deals with the curtailment of renewable power at times of excess energy generation by not dispatching assets that mean the overall generation stack would be above the demand.

For network curtailment, we deal with these volumes using the model of flows around the system in the Balancing Mechanism model.

Is there a volume limit to the Balancing Mechanism? If so, how do you set that?

The volumes in the BM are set by modeling the amount of energy and system balancing the GB system operator must do to keep the grid balanced. We use our wind and demand forecast, along with the capacity of the transmission network in different areas of GB, to predict these. See here.

This determines the 'depth' of the Balancing Mechanism.

Next, we determine how much flexible generation will be on the system: the plants that can flex their output in response to BM actions, and where these will be. We allow batteries, pumped hydro, CCGTs to turn up, and these plus wind to turn down. We then estimate how much of the energy and system actions in a region (dictated by constraint boundaries) that batteries will be to provide, given this competition.

We limit the dispatch of batteries by their duration, day-ahead position, and cycling considerations.

How did we arrive at our carbon derating factors for gas in the CM?

Currently (April 2024), as part of prequalification for the Capacity Market, there is a limit of 550g of Fossil Fuel origin per kWh of electricity generated. This applies to new build, existing, and refurbishing CMUs for the delivery year commencing in 2024, as well as any subsequent delivery years. The Department of Energy Security and Net Zero (DESNZ) have indicated in their latest REMA consultation that they intend to both reduce this limit and to undertake a broader Capacity Market reform. Yet, recent government press releases have stated unabated gas will remain on the system to ensure security of supply.

There are questions about the specifics and timings of emissions limits, as well as how to incentivise low carbon technologies with desirable characteristics. One option DESNZ are considering for the CM consists of 'multiples' which is similar to derating factors for different properties (like de-rating factors in reverse).

We will adapt our Capacity Market model when more information on future auction design is released, but for now we have accounted for carbon through derating factors, using the 550g/kWh limit as a starting point. We have modeled this using a CO2 emissions allowance which drops over time. Plants with emissions below this level (550g/kWh in 2024) have a carbon derating of 100% - i.e. it receives the full CM price for its technology type. Plants with emissions above 550g/kWh have a carbon derating which means they receive less than their full CM price. For instance, if emissions for a generator are halfway between the allowance and the maximum - given by double the allowance - then it will receive a carbon derating of 50%.

We have modeled this using various different rates of decrease for the carbon allowance, as well as carbon maxima that are different multiples of this allowance.

We settle on the factors shown here. If these changes occur too slowly then emissions will not be consistent with emissions targets and Net Zero goals. If these changes occur too quickly then there are concerns around security of supply, and we see the impacts of this through extremely high wholesale prices, extremely high capacity market prices to encourage greater levels of low carbon generation, as well as loss of load. We have therefore settled on yearly allowances and maxima that we believe would make sense from a policy point of view, due to their balance between incentivising low carbon generation whilst maintaining security of supply.

How do you know that the commercial model of storage, and other generator types, is viable?

We have a capacity expansion model that looks at the commercials of newly built plants - i.e., their IRRs and capex, through the forecast horizon. We do this for gas plants (including with CCS), biomass plants, and battery storage. Ie generation types we believe are driven by economics (unlike, say, nuclear). More detail on this here.

New build plants get built if their IRR exceeds the hurdle rate - 10% for batteries, 11% for other thermal plants, with the exception of CCS plants which must meet a 0% hurdle rate (which then grows with the size of the CCS fleet as this technology gets more commercially viable).

Do you model carbon emissions?

In the world view databook, we show the annual carbon intensity of the forecast electricity system.

We do not optimise for net zero in a particular year.