BEGIN:VCALENDAR VERSION:2.0 PRODID:IEEE vTools.Events//EN CALSCALE:GREGORIAN BEGIN:VTIMEZONE TZID:America/New_York BEGIN:DAYLIGHT DTSTART:20250309T030000 TZOFFSETFROM:-0500 TZOFFSETTO:-0400 RRULE:FREQ=YEARLY;BYDAY=2SU;BYMONTH=3 TZNAME:EDT END:DAYLIGHT BEGIN:STANDARD DTSTART:20251102T010000 TZOFFSETFROM:-0400 TZOFFSETTO:-0500 RRULE:FREQ=YEARLY;BYDAY=1SU;BYMONTH=11 TZNAME:EST END:STANDARD END:VTIMEZONE BEGIN:VEVENT DTSTAMP:20251016T124658Z UID:1885E10F-0D56-46A9-A634-C31CA7183639 DTSTART;TZID=America/New_York:20251003T153000 DTEND;TZID=America/New_York:20251003T163000 DESCRIPTION:Abstract: Electricity storage is used for intertemporal price a rbitrage and for balancing supply and demand in real time via frequency re gulation. We present an optimization problem that computes bids for both a rbitrage and frequency regulation and ensures that storage operators can h onor their market commitments at all times for all supply-demand fluctuati on signals in an uncertainty set inspired by market rules. This requiremen t\, initially expressed by an infinite number of nonconvex functional cons traints\, is shown to be equivalent to a finite number of deterministic co nstraints. The model can account for intraday trading and\, with a solutio n 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 20 20 through 30 June 2024 on European electricity markets participating in b oth arbitrage and frequency regulation more than doubles profits and almos t halves energy storage output compared to arbitrage alone.\n\nBio: Dirk L auinger is a postdoc at the MIT Energy Initiative and the Sloan School of Management researching mathematical optimization for electricity storage a nd transportation. He joined Sungho Shin's group in September 2024 to work on storage investment problems\, after a two-year postdoc with Andy Sun w orking on storage operations and on ARPA-E's Grid Optimization Competition . In June 2022\, he completed his PhD at the Risk Analytics and Optimizati on 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 i n Energy Management and Sustainability and a BSc in Electrical and Electro nics Engineering from EPFL.\n\nRoom: E432\, Bldg: Innovation\, 82 Universi ty Pl\, Burlington\, Vermont\, United States\, 05405 LOCATION:Room: E432\, Bldg: Innovation\, 82 University Pl\, Burlington\, Ve rmont\, United States\, 05405 ORGANIZER:schevali@uvm.edu SEQUENCE:21 SUMMARY:Dirk Lauinger: On electricity storage\, robust optimization\, and t he law: Reliable multi-market bidding URL;VALUE=URI:https://events.vtools.ieee.org/m/503367 X-ALT-DESC:Description: <br /><p>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 com putes bids for both arbitrage and frequency regulation and ensures that st orage operators can honor their market commitments at all times for all su pply-demand fluctuation signals in an uncertainty set inspired by market r ules. This requirement\, initially expressed by an infinite number of nonc onvex functional constraints\, is shown to be equivalent to a finite numbe r of deterministic constraints. The model can account for intraday trading and\, with a solution time of under 5 seconds\, may serve as a building b lock for more complex trading strategies. Such strategies become necessary as battery capacity exceeds the demand for frequency regulation. In a bac k test from 1 July 2020 through 30 June 2024 on European electricity marke ts participating in both arbitrage and frequency regulation more than doub les profits and almost halves energy storage output compared to arbitrage alone.</p>\n<p>Bio: Dirk Lauinger is a postdoc at the &nbsp\;MIT Energy In itiative and the Sloan School of Management researching mathematical optim ization 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 r obust optimization for vehicle-to-grid and was advised by Daniel Kuhn and Fran&ccedil\;ois Vuille. He hold a MSc in Energy Management and Sustainabi lity and a BSc in Electrical and Electronics Engineering from EPFL.</p> END:VEVENT END:VCALENDAR