Coordinated Trading Strategies for Battery Storage in Reserve and Spot Markets
Paul E. Seifert, Emil Kraft, Steffen Bakker, Stein-Erik Fleten

TL;DR
This paper develops a stochastic programming approach using stochastic dual dynamic programming to optimize coordinated trading strategies for battery storage across multiple electricity markets, considering uncertainties and market interdependencies.
Contribution
It introduces a multi-stage stochastic model incorporating frequency reserve, day-ahead, and intraday markets, demonstrating the benefits of coordinated bidding for energy storage.
Findings
Capacity reservation in frequency reserve dominates cycling in spot markets.
Coordination can increase value by up to 12.5% in adjusted price environments.
The method effectively captures market interdependencies and uncertainties.
Abstract
Quantity and price risks are key uncertainties market participants face in electricity markets with increased volatility, for instance, due to high shares of renewables. From day ahead until real-time, there is a large variation in the best available information, leading to price changes that flexible assets, such as battery storage, can exploit economically. This study contributes to understanding how coordinated bidding strategies can enhance multi-market trading and large-scale energy storage integration. Our findings shed light on the complexities arising from interdependencies and the high-dimensional nature of the problem. We show how stochastic dual dynamic programming is a suitable solution technique for such an environment. We include the three markets of the frequency containment reserve, day-ahead, and intraday in stochastic modelling and develop a multi-stage stochastic…
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Taxonomy
TopicsElectric Vehicles and Infrastructure · Advanced Battery Technologies Research · Extraction and Separation Processes
