We run the model over 2021 & 2022 and compare our half-hourly price to N2EX day-ahead hourly prices. We replace some of the inputs to the model with historic data to get an assessment of 'the model' (as opposed to the inputs).
We compare a data point every half hour (our forecast) to a data point every hour (the N2EX day-ahead price). We take that hourly data point for and make two per hour so we can compare every forecasted data point.
We normalize the model as much as possible - so give it real historic data and see what the model generates. This allows us to compare our model to historic data and hope to achieve something vaguely close.
- Using daily SAP gas price (this means the shapes track)
- Actual wind data
- Plant availability (via MEL data) for CCGTs and OCGTs
- We use historical demand data
- We underpredict absolute prices by an average of £30/MWh and intraday spreads by a similar amount.
- Both 2021 and 2022 saw far more intraday volatility than our model predicts. There are a few reasons for this:
- The Russian invasion of Ukraine - and linked record high gas prices - added a significant risk premium to market operators.
- The gas and electricity markets were in contango (future markets were worth more than spot markets) - and peak power especially was over-valued.
- In periods of tightness, particularly over £500/MWh, a scarcity premium emerges in power markets.
- Considering these factors, a huge risk premium was priced into the market: this is not captured in our fundamentals model.
- We don't model CCGT ramp rates in our fundamentals model. This also explains some of the shortfalls in the intraday price volatility.
Updated 1 day ago