From Intraday Orderbook to Imbalance Price: Understanding Cross-Market Interaction

2026-09-29

AI Summary

This study addresses the unclear interaction mechanisms between intraday and balancing electricity markets and the inherent difficulty of predicting imbalance prices. For the first time, it systematically quantifies the impact of intraday order book features on imbalance prices. By employing order book representations such as the volume-weighted average price (VWAP), combined with probabilistic modeling and multi-product neighborhood comparison techniques, this work thoroughly analyzes cross-market interaction patterns in Germany and Austria. Results demonstrate that VWAP achieves optimal predictive performance when integrating information from adjacent products, while incorporating full historical data significantly enhances overall accuracy. This research effectively reveals country-dependent differences in market interaction mechanisms, establishing a novel paradigm for cross-national imbalance price forecasting.

Abstract

Power systems with increasing variable renewable generation face greater uncertainty in scheduling and balancing. Intraday and balancing electricity markets facilitate position adjustments and real-time balancing close to delivery. As delivery approaches, continuous intraday market participants exposed to imbalance settlement adjust their positions by trading additional volumes to reduce their imbalance exposure. We conjecture that positions remaining open after intraday trading, together with demand and supply uncertainties affecting physical market participants, influence price formation in the balancing market. This cross-market interaction is, however, rarely studied. To understand this interaction, this paper uses probabilistic modeling to examine how intraday orderbook information reflects subsequent imbalance price formation in Germany and Austria. We compare orderbook representations based on open, high, low, close, and volume, Volume-Weighted Average Price (VWAP), and last mid price across multiple horizons. Each representation is evaluated using the self product, neighboring products, and the product from the neighboring country. We then compare the best orderbook setting with fundamental feature sets and their combinations, followed by an ablation study of the available training history. We show that VWAP with neighboring products provides the best performance in both countries. Combining orderbook and fundamental information reduces testing loss in Germany but increases it in Austria. Using all available observations provides the best overall performance, while excluding 2022 can reduce loss for extreme price samples. These results reveal and help explain country-dependent interactions between the intraday and balancing markets.

Problem

• intraday market
• balancing market
• imbalance price
• cross-market interaction
• orderbook

Innovation

• Probabilistic Modeling
• Cross-Market Interaction
• Orderbook Representation
• Volume-Weighted Average Price
• Imbalance Price