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Optimal Coordinated Control of Multiple Battery Energy Storage Systems for Primary Frequency Regulation

机译:一次频率调节的多个电池储能系统的最优协调控制

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摘要

In this paper, we consider a battery aggregator that coordinates a number of distributed battery energy storage systems (BESSs) to provide primary frequency control service in the ancillary service market. In particular, we propose a profit-maximizing BESS coordination strategy that is concerned with two operational phases, namely a frequency regulation phase and a state-of-charge (SoC) recovery phase. Regarding the frequency regulation phase, we minimize the regulation failure penalty by optimally coordinating the operation of multiple BESSs in response to local frequency deviations. The proposed coordination algorithm is “online optimal” in the sense that it does not require any knowledge of the future information, and yet achieves exactly the same optimal performance as if the entire future information is known. On the other hand, during idle periods, the BESSs shall recover their SoCs to a proper range to avoid regulation failure in the next frequency excursion event. We propose a SoC recovery strategy that is not only optimal, but also state invariant and separable in the sense that the target SoC range of each BESS neither varies with its own SoC nor depends on the operation of other BESSs. As such, the target SoC ranges can be calculated once and for all, resulting in extremely low run-time complexity. Numerical results based on real power system frequency measurement data show that the proposed algorithm significantly outperforms a number of benchmark algorithms.
机译:在本文中,我们考虑了一个电池聚合器,该电池聚合器可协调许多分布式电池储能系统(BESS),以在辅助服务市场中提供主要的频率控制服务。特别是,我们提出了一个利润最大化的BESS协调策略,该策略涉及两个操作阶段,即频率调节阶段和荷电状态(SoC)恢复阶段。关于频率调节阶段,我们通过响应于局部频率偏差来最佳地协调多个BESS的运行,从而将调节失败的损失最小化。在不需要任何未来信息知识的情况下,所提出的协调算法是“在线最优”的,并且可以实现与已知整个未来信息完全相同的最优性能。另一方面,在空闲期间,BESS必须将其SoC恢复到适当的范围,以避免在下一个频率偏移事件中调节失败。我们提出的SoC恢复策略不仅是最佳的,而且在每个BESS的目标SoC范围既不随其自己的SoC改变也不依赖于其他BESS的操作的意义上,又是状态不变且可分离的。这样,就可以一劳永逸地计算出目标SoC范围,从而大大降低了运行时的复杂度。基于实际电力系统频率测量数据的数值结果表明,该算法明显优于许多基准算法。

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