Operational use of marginal cost curves for a hydropower producer trading in the intraday market

Dideriksen, Ane Froyen; Sekkesater, Susanne; Fleten, Stein–Erik; Aasgord, Ellen Krohn; Skjelbred, Hans-Ivar

doi:10.1109/eem.2019.8916213

Cited by 1 publication

(2 citation statements)

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“…Engmark et al (2018) propose a trading strategy for a hydro power producer on the day-ahead, intraday and balancing market. Dideriksen et al (2019) consider trading strategies for a hydropower producer on the intraday market. Koch (2021) uses the intraday market to build up a position to be cleared on the balancing market, thus arbitraging between the two markets.…”

Section: Introductionmentioning

confidence: 99%

“…We take great care to accurately model market mechanisms, the exact clearing algorithm, and the sequence of information. To the best of our knowledge Skajaa et al (2015); Martin and Otterson (2018); Engmark et al (2018); Bertrand and Papavasiliou (2019); Kuppelwieser and Wozabal (2020); Dideriksen et al (2019) are the only other papers that capture the realities of continuous trading in similar detail. In particular, apart from Skajaa et al (2015); Engmark et al (2018); Bertrand and Papavasiliou (2019); Dideriksen et al (2019);Koch (2021), this is the first paper that evaluates a trading strategy based on detailed order book data, which is different from the extant literature that discretizes the trading to 1 min or 15 min brackets to be able to deal with the shear amount of order data (e.g., Glas et al 2019Glas et al , 2020Kath and Ziel 2020).…”

Section: Introductionmentioning

confidence: 99%

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Intraday power trading: toward an arms race in weather forecasting?

Kuppelwieser

Wozabal²

2022

OR Spectrum

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We propose the first speculative weather-based algorithmic trading strategy on a continuous intraday power market. The strategy uses neither production assets nor power demand and generates profits purely based on superior information about aggregate output of weather-dependent renewable production. We use an optimized parametric policy based on state-of-the-art intraday updates of renewable production forecasts and evaluate the resulting decisions out-of-sample for one year of trading based on detailed order book level data for the German market. Our strategies yield significant positive profits, which suggests that intraday power markets are not semi-strong efficient. Furthermore, sizable additional profits could be made using improved forecasts of renewable output, which implies that the quality of forecasts is an important factor for profitable trading strategies. This has the potential to trigger an arms race for more frequent and more accurate forecasts, which would likely lead to increased market efficiency, more reliable price signals, and more liquidity.

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Section: Introductionmentioning

confidence: 99%