Coordinated Trading Strategies for Battery Storage in Reserve and Spot Markets

Paul E. Seifert,Emil Kraft,Steffen Bakker,Stein-Erik Fleten

arXiv · Methodology（2024）

Cited 0|Views8

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 program. Prices are represented in a multidimensional Markov Chain, following the scheduling of the markets and allowing for time-dependent randomness. Using the example of a battery storage in the German energy sector, we provide valuable insights into the technical aspects of our method and the economic feasibility of battery storage operation. We find that capacity reservation in the frequency containment reserve dominates over the battery's cycling in spot markets at the given resolution on prices in 2022. In an adjusted price environment, we find that coordination can yield an additional value of up to 12.5

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【要点】：本文研究了如何通过协调交易策略增强电池储能同时在储备和现货市场的多市场交易集成，创新地应用了随机双重动态规划方法解决高维问题。

【方法】：研究采用了随机双重动态规划方法来解决电力市场中储能资产的多市场交易策略问题。

【实验】：以德国能源市场为例，通过频率 containment 储备、日前和日内市场构建多阶段随机程序，运用价格的多维马尔可夫链表示市场调度中的时间相关随机性，实验结果显示在2022年的价格环境下，频率 containment 储备的容量预订比电池在现货市场的循环更有优势；在调整后的价格环境中，协调策略可带来最高12.5%的附加价值。

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