Providing multiple services on multiple time scales with energy storage

储能是电力系统灵活性的重要来源。它的用途包括平衡可再生能源的可变性，降低峰值功耗以避免使用昂贵的调峰电厂，通过将需求从白天转移到夜晚来提高系统效率，以及提供调节以保持快速时间尺度的稳定性。当前的挑战是选择存储设备应该提供多少服务。例如，如果电池在前一天的市场中将其容量的一部分用于旋转储备，则该容量将不能用于提供真实的调节。尽管电池、飞轮和超级电容器等技术的成本正在下降，但存储仍然很昂贵。这使得从已安装的存储资产中获得最大价值变得至关重要，只有当存储设备提供多种服务时，才能实现其全部价值。在拟议的研究中，我们将设计算法，使能源存储能够同时最佳地提供多种服务。我们还将设计存储策略，以在多个不同的市场中竞标其容量。我们将把这个问题建模为一个动态程序。动态编程先前已用于获得用于提供个别服务的能量存储的控制策略。我们将把这项工作扩展到存储提供多种服务的情况，在可能的情况下寻求分析策略，并在其他情况下使用近似技术。

Energy storage is an important source of flexibility in electric power systems. Its uses include balancing renewable variability, reducing peak power consumption to avoid using expensive peaker plants, improving system efficiency by shifting demand from day to night, and providing regulation to maintain stability on fast time scales. A current challenge is choosing how much of each service a storage device should provide. For example, if a battery commits a portion of its capacity in a day-ahead market for spinning reserve, then that capacity will not be available for providing regulation in real time. Although the cost of technologies such as batteries, flywheels, and supercapacitors is dropping, storage remains expensive. This makes it critical to derive maximum value from installed storage assets, and the full value of a storage device can only be realized if it provides multiple services. In the proposed research, we will design algorithms that enable energy storage to optimally provide multiple services simultaneously. We will also design strategies for storage to bid its capacity in multiple, distinct markets. We will model the problem as a dynamic program. Dynamic programming has been previously used to obtain control policies for energy storage providing individual services. We will extend this line of work to the case of storage providing multiple services, seeking analytical policies where possible and using approximate techniques in other cases.