Power Markets

Session chair: Farzaneh Pourahmadi
Technical University of Denmark – DTU

AI is increasingly used in electricity markets for applications such as forecasting, bidding, multi-market trading, and demand flexibility. Yet, most existing approaches remain task-specific and can struggle to generalize across changing market conditions, market designs, products, and participants. This session will bring together recent developments in AI for power markets and discuss where foundation models may offer genuine advantages over classical AI approaches, where they may not, and what methodological and practical advances are needed for their reliable deployment. Ultimately, the session will explore whether a “MarketFM” could emerge as a useful foundation for future market forecasting and decision-making.

Foundation Model for Electricity Price Forecasting

Speaker: Runyao Yu – TU Delft and AIT

Electricity price forecasting in Europe presents unique challenges due to increasing renewable generation variability, market integration, and the continent’s physically interconnected power system. While recent advances in foundation models have led to substantial improvements in general time series forecasting, most existing approaches do not incorporate prior graph knowledge from the transmission topology, which can limit their ability to exploit meaningful cross-region dependencies in interconnected power systems, motivating a domain-specific foundation model. In this presentation, we show how to design and use the pretrained foundation model for probabilistic electricity price forecasting.