Intraday Renewable Electricity Trading: Advanced Modeling and Optimal Control

Glas, Silke; Kiesel, Rüdiger; Kolkmann, Sven; Kremer, Marcel; Luckner, Nikolaus Graf von; Ostmeier, Lars; Urban, Karsten

doi:10.1007/978-3-030-27550-1_59

Cited by 6 publications

(6 citation statements)

References 5 publications

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“…Wozabal and Rameseder (2020) propose trading strategies for a storage that arbitrages between Spanish day-ahead and intraday markets. Furthermore, Kath and Ziel (2020) explore optimal order execution strategies with the aim to minimize liquidity cost and Glas et al (2019Glas et al ( , 2020 study optimal VRES trading strategies on the intraday market in an optimal control setting. Finally, Bertrand and Papavasiliou (2019) use reinforcement learning to optimize a Markovian strategy for an electricity storage on the German intraday market for power.…”

Section: Introductionmentioning

confidence: 99%

“…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

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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%

Section: Introductionmentioning

confidence: 99%

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

Kuppelwieser

Wozabal²

2022

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“…[10][11][12][13] examine the impact of renewable power generation and its forecast errors on intraday electricity prices; Refs. [14][15][16][17] derive optimal trading strategies for an agent who aims at marketing both renewable and conventional power on the intraday market; Refs. [7,18,19] provide forecasting studies for intraday electricity prices; Refs.…”

Section: Introductionmentioning

confidence: 99%

Intraday Electricity Pricing of Night Contracts

2020

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This paper investigates the intraday electricity pricing of 15-min. contracts in night hours. We tailor a recently introduced econometric model with fundamental impacts, which is successful in describing the pricing of day contracts. Our estimation results show that the mean reversion and the positive price impact of neighboring contracts are generic features of the price formation process on the intraday market, independent of the time of day. Intraday auction prices have higher explanatory power for the pricing of night than day contracts, particularly, for the first and last 15-min. contract in a night hour. Intradaily updated forecasts of wind power infeed are the only significant fundamental factors for intraday electricity prices at night. Neither expected conventional capacities nor the slope of the merit order curve contribute to explaining price dynamics. Overall, we conclude that fundamentals lose in importance in night hours and the 15-min. intraday market is rather driven by price information.

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“…The starting point of this paper (which builds upon and extends [9]) is a statistical analysis of EPEX SPOT data, which shows that some of the model assumptions in [1] are in fact not satisfied under real market conditions. Thus, we introduce a more sophisticated model.…”

Section: Introductionmentioning

confidence: 99%

Intraday renewable electricity trading: advanced modeling and numerical optimal control

et al. 2020

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As an extension of (Progress in industrial mathematics at ECMI 2018, pp. 469-475, 2019), this paper is concerned with a new mathematical model for intraday electricity trading involving both renewable and conventional generation. The model allows to incorporate market data e.g. for half-spread and immediate price impact. The optimal trading and generation strategy of an agent is derived as the viscosity solution of a second-order Hamilton-Jacobi-Bellman (HJB) equation for which no closed-form solution can be given. We construct a numerical approximation allowing us to use continuous input data. Numerical results for a portfolio consisting of three conventional units and wind power are provided.

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Intraday Renewable Electricity Trading: Advanced Modeling and Optimal Control

Cited by 6 publications

References 5 publications

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

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

Intraday Electricity Pricing of Night Contracts

Intraday renewable electricity trading: advanced modeling and numerical optimal control

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