Fundamental Approaches to Dutch Electricity Price Formation
A Structural Approach Benchmarked Against a Hybrid Merit-Order Calibration, with Battery Storage Valuation
J.A. van Delden (TU Delft - Electrical Engineering, Mathematics and Computer Science)
R.A. Verzijlbergh – Mentor (TU Delft - Technology, Policy and Management)
L.J. de Vries – Graduation committee member (TU Delft - Technology, Policy and Management)
J. Iori – Graduation committee member (TU Delft - Aerospace Engineering)
Arnoud Higler – Mentor (Shell International Global Energy Solutions)
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Abstract
This thesis asks how much of the Dutch day-ahead electricity price can be explained by economic dispatch models with no fitted parameters, and what the remaining gap reveals about the market.
The Dutch market combines a gas-dominated thermal fleet, roughly 13 GW of combined heat and power (CHP) with heat-driven must-run obligations, and solar PV capacity that grew 26% over 2023–2025, most of it rooftop and largely invisible in metered generation. Against this background I build a ladder of economic dispatch variants that add structural realism step by step: CHP constraints, unit commitment, procurement-informed mark-ups, and four alternative treatments of cross-border trade. These are compared with a 44-parameter hybrid merit-order stack (MOS) calibrated on 2023 EPEX prices (RMSE 36.75 EUR/MWh), with 2024 and 2025 held out.
The cross-border treatment decides the outcome. Prescribing observed flows in a single-node LP sharply increases the error (RMSE 103 EUR/MWh), whereas letting the LP trade endogenously against the five neighbours’ observed day-ahead prices under NTC limits reaches RMSE 22.7–24.5 EUR/MWh in all three years with no fitted parameters, better than the calibrated MOS in every year. Because the neighbour prices are realised values for the same delivery hours, these two-node results are ex-post reconstructions rather than forecasts. A 5-parameter correction on the single-node model, which rescales its solar term by CBS-reported PV capacity, also outperforms the MOS on 2025 out-of-sample data (38.1 versus 40.6 EUR/MWh). Within the window tested, structural parameters proved more stable than fitted coefficients.
An exhaustive ablation of the calibrated model identifies CHP must-run as the dominant parameter group. Storage arbitrage, used as an economic test, ranks the models differently from RMSE: models that score best on price level do not necessarily preserve the spread a battery trades on. Making storage endogenous in the dispatch produces a self-cannibalisation curve: scaling a four-hour fleet from 0.5 to 20 GWh cuts arbitrage value from 17.9 to 5.4 EUR/kWh/yr, interconnection retains 1.9–3.4 times the isolated-market value, and every endogenous value falls below the annualised capital cost of roughly 34 EUR/kWh/yr. Day-ahead arbitrage alone therefore does not finance storage in this model; ancillary and imbalance revenues are out of scope.
The main limitations are the two-year out-of-sample window and the reliance on observed neighbour prices. Within those bounds, the practical conclusion is that in interconnected markets with public neighbour-price and NTC data, two node coupling should be the first structural lever attempted before any calibration.