联合频率和能源市场中的电池储能双时标运行策略

Qianli Ma;Wei Wei;Shengwei Mei
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摘要

可再生能源在现代电力系统中的渗透率越来越高,这就要求储能系统在多种调节服务中承担更多责任。电池储能系统(BESS)具有快速响应能力,适用于削峰填谷和提供频率支持。本文研究了 BESS 在频率调节和能源市场中的协调投标策略。由于频率调节和能源套利行动的时间尺度不同,在其中一个市场使用的容量会影响另一个市场的可用容量和收益,因此存在挑战。本文提出了一个双时间尺度决策框架,提供能源市场的每小时基本功率出价和频率调节市场的容量出价,以及每隔几秒对自动发电控制(AGC)信号的实时响应。在精细时间尺度上,我们采用阈值策略,根据电池寿命生成 AGC 响应。在粗时间尺度上,我们建立了一个随机动态编程模型,并在不准确预测市场价格的情况下优化竞标策略。为了在线求解随机动态编程模型,我们开发了一种基于仿真的策略改进方法,利用启发式基本策略逼近状态-行动值函数。从理论上证明了模拟带来的性能改进特性。我们进行了全面的案例研究来验证所提方法的有效性,并分析了电价和电池 $E/P$ 比率对经济的影响。实证测试表明,当 $E/P$ 比率为 3$\sim$5 时,BESS 在整个生命周期内可获得更高的净收益。
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A Two-Timescale Operation Strategy for Battery Storage in Joint Frequency and Energy Markets
The growing penetration of renewable energy in modern power systems requires energy storage to take on more responsibilities in multiple regulation services. Battery energy storage system (BESS) possesses fast response capability and is suitable to shave peak demand and provide frequency support. This article studies coordinated bidding strategies of BESS in frequency regulation and energy markets. Challenge arises from the fact that frequency control and energy arbitrage actions are taken in different timescales, and the capacity used in either market affects the available capacity and revenue in the other one. This article proposes a two-timescale decision framework, offering the hourly base-power bid in the energy market and capacity bid in the frequency regulation market, as well as real-time responses to the automatic generation control (AGC) signal every few seconds. In the fine timescale, we employ a threshold policy to generate AGC response accounting for battery lifespan. In the coarse timescale, we establish a stochastic dynamic programming model and optimize the bidding policy without exact forecasts of market prices. To solve the stochastic dynamic programming model online, a simulation-based policy improvement method is developed to approximate the state-action value function using a heuristic base policy. The performance improvement property brought by simulation is theoretically proven. We carry out comprehensive case studies to validate the effectiveness of the proposed method and analyze the economic impact of electricity prices and battery $E/P$ ratio. Empirical tests show that with an $E/P$ ratio of 3 $\sim$ 5, the BESS gains a higher net revenue across the lifespan.
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