Electricity price forecasting is crucial for market participants but remains difficult because prices are volatile, market-specific, and closely tied to anticipated system conditions. Existing supervised methods depend largely on market-specific historical data, limiting their use in newly established or data-scarce markets.
arXiv:2609.23223v1 Announce Type: cross
Abstract: Day-ahead electricity price forecasts support trading and storage decisions, but for battery arbitrage predicting intraday price spreads is more rele...
By Arkadiusz Lipiecki, Nikolaos Kourentzes, Rafal Weron
arXiv:2608. 01290v1 Announce Type: new Abstract: Time-series foundation models (TSFMs) such as Chronos have demonstrated strong forecasting capabilities across domains, yet adapting them to institutionally fragmented settings, where data cannot be centralized due to regulatory, competitive, or sovereignty constraints, remains unexplored.
By Amit Sharma, Nitin Auluck, Akramul Azim
The study evaluates nine foundation model variants against two leading electricity price forecasting benchmarks across Germany, Poland, and Spain for 2021‑2025. Only the TabPFN models consistently outperform the benchmarks in both point and probabilistic accuracy, yet their economic advantage varies with bidding strategy and risk tolerance. The results indicate that foundation models cannot universally replace market‑specific models; their usefulness depends on the chosen architecture and the particular decision problem.
By Arkadiusz Lipiecki, Rafa{\l} Weron
arXiv:2606. 27032v1 Announce Type: cross Abstract: Energy trading decisions depend not only on current market prices, but also on expected future market conditions, and operational constraints.
By Jesper Klicks, Sander Vr\v{z}ina, Vincent Fran\c{c}ois-Lavet
arXiv:2405.07359v2 Announce Type: replace
Abstract: Accurate prediction of electricity day-ahead prices is essential in competitive electricity markets. Although stationary electricity-price forecast...
By Antonio Malpica-Morales, Miguel A. Dur\'an-Olivencia, Serafim Kalliadasis