Dirk Lauinger: On electricity storage, robust optimization, and the law: Reliable multi-market bidding

#energy-storage #engineering #pes

Abstract: Electricity storage is used for intertemporal price arbitrage and for balancing supply and demand in real time via frequency regulation. We present an optimization problem that computes bids for both arbitrage and frequency regulation and ensures that storage operators can honor their market commitments at all times for all supply-demand fluctuation signals in an uncertainty set inspired by market rules. This requirement, initially expressed by an infinite number of nonconvex functional constraints, is shown to be equivalent to a finite number of deterministic constraints. The model can account for intraday trading and, with a solution time of under 5 seconds, may serve as a building block for more complex trading strategies. Such strategies become necessary as battery capacity exceeds the demand for frequency regulation. In a back test from 1 July 2020 through 30 June 2024 on European electricity markets participating in both arbitrage and frequency regulation more than doubles profits and almost halves energy storage output compared to arbitrage alone.

Bio: Dirk Lauinger is a postdoc at the  MIT Energy Initiative and the Sloan School of Management researching mathematical optimization for electricity storage and transportation. He joined Sungho Shin's group in September 2024 to work on storage investment problems, after a two-year postdoc with Andy Sun working on storage operations and on ARPA-E's Grid Optimization Competition. In June 2022, he completed his PhD at the Risk Analytics and Optimization Chair at EPFL. His thesis focused on robust optimization for vehicle-to-grid and was advised by Daniel Kuhn and François Vuille. He hold a MSc in Energy Management and Sustainability and a BSc in Electrical and Electronics Engineering from EPFL.

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• Starts 26 September 2025 04:00 AM UTC
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