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Stochastic Optimization of Trading Strategies in Sequential Electricity Markets

Kraft, Emil ORCID iD icon; Russo, Marianna; Keles, Dogan; Bertsch, Valentin


Quantity and price risks determine key uncertainties market participants face in electricity markets with increased volatility, for instance due to high shares of renewables. In the time from day-ahead until real-time, there lies a large variation in best available information, such as between forecasts and realizations of uncertain parameters like renewable feed-in and electricity prices. This uncertainty reflects on both the market outcomes and the quantity of renewable generation, making the determination of sound trading strategies across different market segments a complex task. The scope of the paper is to optimize day-ahead and intraday trading decisions jointly for a portfolio with controllable and volatile renewable generation under consideration of risk. We include a reserve market, a day-ahead market and an intraday market in stochastic modeling and develop a multi-stage stochastic Mixed Integer Linear Program. We assess the profitability as well as the risk exposure, quantified by the conditional value at risk metric, of trading strategies following different risk preferences. We conclude that a risk-neutral trader mainly relies on the opportunity of higher expected profits in intraday trading, whereas risk can be hedged effectively by trading on the day-ahead. ... mehr

Volltext §
DOI: 10.5445/IR/1000134346
Veröffentlicht am 23.06.2021
Cover der Publikation
Zugehörige Institution(en) am KIT Institut für Industriebetriebslehre und Industrielle Produktion (IIP)
Publikationstyp Forschungsbericht/Preprint
Publikationsmonat/-jahr 06.2021
Sprache Englisch
Identifikator ISSN: 2196-7296
KITopen-ID: 1000134346
Verlag Karlsruher Institut für Technologie (KIT)
Umfang 42 S.
Serie Working Paper Series in Production and Energy ; 58
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