Battery Storage Optimization on the German Continuous Intraday Market: An Experimental Analysis under Consideration of Price Uncertainties

This article uses an experimental approach to examine the extent to which price fluctuations influence the profitability of electricity storages operating on the German Continuous Intraday Market. For this reason, we are extending our previous research and analyzing the trade-off between storage capacity and price forecast uncertainty with regard to arbitrage profitability. Using a genetic algorithm, we optimize buy and sell decisions for different battery storage sizes and simulated price forecast uncertainties over the year 2021. Our results show that a storage management strategy generated by the genetic algorithm enables significant arbitrage revenues, which rise in particular with increasing storage capacity. However, with an increasing battery size, decreasing marginal profits are to be expected. Price uncertainties due to forecast errors also reduce the gains, but their influence on profit remains moderate compared to the storage size. The genetic algorithm used provides an intelligent strategy for optimizing storage usage even under uncertain market conditions.

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Publication Details

Journal
Complex Systems Informatics and Modeling Quarterly
Published
2025-12-31
DOI
https://doi.org/10.7250/csimq.2025-45.01
Primary Topic
Smart Grid Energy Management
Type
article
Field-Weighted Citation Impact
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article

Battery Storage Optimization on the German Continuous Intraday Market: An Experimental Analysis under Consideration of Price Uncertainties

Richard Lackes, Mathis Wilz
Complex Systems Informatics and Modeling Quarterly
Smart Grid Energy Management
article

Battery Storage Optimization on the German Continuous Intraday Market: An Experimental Analysis under Consideration of Price Uncertainties

Richard Lackes, Mathis Wilz
article en

Abstract

This article uses an experimental approach to examine the extent to which price fluctuations influence the profitability of electricity storages operating on the German Continuous Intraday Market. For this reason, we are extending our previous research and analyzing the trade-off between storage capacity and price forecast uncertainty with regard to arbitrage profitability. Using a genetic algorithm, we optimize buy and sell decisions for different battery storage sizes and simulated price forecast uncertainties over the year 2021. Our results show that a storage management strategy generated by the genetic algorithm enables significant arbitrage revenues, which rise in particular with increasing storage capacity. However, with an increasing battery size, decreasing marginal profits are to be expected. Price uncertainties due to forecast errors also reduce the gains, but their influence on profit remains moderate compared to the storage size. The genetic algorithm used provides an intelligent strategy for optimizing storage usage even under uncertain market conditions.

Complex Systems Informatics and Modeling Quarterly(45)
TU Dortmund University (DE)
Openalex Percentile: Top 41%
Smart Grid Energy Management
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