Optimizing trading of electric vehicle charging flexibility in the continuous intraday market under user and market uncertainties

Raviteja Chemudupaty, Timothée Hornek, Ivan Pavić and Sergio Potenciano Menci

Applied Energy, 2025, vol. 381, issue C, No S0306261924024875

Abstract: The rise in electric vehicles (EVs) challenges energy suppliers with unpredictable charging behavior, making demand forecasts less accurate and increasing financial risks from power imbalances. In Europe, retailers can trade these imbalances in short-term markets like the continuous intraday (CID) market. By controlling EV charging times, suppliers can shift charging to periods with lower prices, potentially benefiting financially. However, the financial gains from trading this flexibility in the CID market remain uncertain due to EV user behavior and price fluctuations. In this study, we develop and test trading strategies designed to manage the power needs of a fleet of 1000 EVs across different segments of short-term electricity markets, focusing on the day-ahead (DA) auction, and the CID market. To address EV-use uncertainty, we take an initial EV charging flexibility forecast for the DA auction, and an updated forecast for the CID market. We find that trading in the CID market reduces the overall cost of making power purchases by capitalizing on the flexibilities of EV charging times. Our results suggest that energy suppliers trading in the CID market significantly reduce their financial risk, even when there are high margins of error in EV flexibility forecasts. In our scenario with the highest deviation between the DA and intraday (ID) flexibility metrics, applying the best CID strategies yielded an average yearly profit of €37.52 and €4,840.63 in 2019 and 2022 respectively. In comparison to the baseline strategy, which clears volumes as imbalances, the corresponding financial savings amounted to €1978.52 and €16,632.25, respectively.

Keywords: Electric vehicle flexibility; Multi-stage optimization; Continuous intraday market; Electric vehicle user uncertainty; Short-term electricity price forecasting (search for similar items in EconPapers)
Date: 2025
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DOI: 10.1016/j.apenergy.2024.125103

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