Characterizing capacity of controllable DERs to provide energy storage service to the power grid

本项目的目的是开发一种方法来估计分布式能源向电网提供需求侧服务的能力，特别是来自一组灵活负载的虚拟储能(VES)。虚拟储能是指空调等负荷的电力消耗的微小受控变化，因此产生的变化看起来就像是对电网其余部分的电池充电和放电。虚拟储能预计将比真正的电池便宜，因为不需要新的硬件；唯一的变化是软件。部署这项技术的一个瓶颈是缺乏工具来回答有关大负荷集合的等效电池容量的问题，例如，我们需要多少智能家用空调才能提供与5兆瓦/3兆瓦/小时锂离子电池相同的服务？该项目将开发数学技术来回答这些问题和更多问题，从而实现未来智能负荷的电网运营和规划。因此，该项目将有助于提高国家电力供应的可靠性和弹性。所提出的方法的一个明智的优点是，它们是“未来的证据”，因为它们独立于用于协调负载的算法。另一个智能优点是所提出的数据驱动方法，它不需要难以获得的DER的简单降阶模型。该项目的一个更广泛的影响是，通过为运营和规划提供计算方法，帮助电网运营商采用智能负荷技术。其他更广泛的影响包括用研究成果改进国际和平研究所的课程，并吸引代表不足和少数族裔的本科生参加STEM研究。由于每个负载在提供网格支持时都必须满足用户的本地服务质量，因此大量负载提供VES的能力与这些本地服务质量约束有着复杂的依赖关系。除了兆瓦/千瓦时数字外，电网运营商还需要确定对于一组负荷来说，什么样的需求偏差是可行的，这样就不会有人违反当地的限制。例如，当空调提供需求侧服务时，室内温度不应变得太热或太冷。应对这些挑战有两个不同的时间尺度：短期规划(以小时为单位)和长期规划(以月为单位)。对于短期计划，提出了一个确定性的框架，其中可行的需求轨迹通过一组低维约束来描述。一个关键的创新是通过集合平均将由于加载锁定约束而产生的高维整数约束缩减为用于集合的低维凸约束。对于长期规划，提出了一个基于谱密度的统计框架，该框架能够表征可行的需求偏差信号的所有可能的样本路径。该奖项反映了NSF的法定使命，并通过使用基金会的智力优势和更广泛的影响审查标准进行评估，被认为值得支持。

The aim of this project is to develop methods to estimate the capacity of distributed energy resources to provide demand side services to the power grid, in particular, Virtual Energy Storage (VES) from a collection of flexible loads. Virtual energy storage refers to small controlled changes in the electrical power consumption of loads, such as air conditioners, so that the resulting variation appears like the charging and discharging of a battery to the rest of the power grid. Virtual energy storage is expected to be cheaper than real batteries since no new hardware is needed; the only change is software. A bottleneck in deploying this technology has been the lack of tools to answer questions about the equivalent battery capacity of large collections of loads, such as, "How many smart residential air conditioners do we need to provide the same service as a 5MW/3MWh Li-ion battery?". The project will develop mathematical techniques to answer such questions and more, and thereby enable grid operation and planning with smart loads of the future. The project will thus contribute to increasing the reliability and resiliency of the nation’s electricity supply. An intellectual merit of the proposed methods is that they are "future proof" since they are independent of the algorithms used to coordination the loads. Another intellectual merit is the data-driven methods proposed, which do not need simple reduced order models of DERs that are difficult to obtain. A broader impact of the project is to help grid operators adopt smart load technology by providing computational methods for operation and planning. Other broader impacts include enhancements to the curriculum in the PI's institution with research results and attracting underrepresented and minority undergraduates to STEM research. Because each load must satisfy the consumer's local quality of service in providing grid support, the capacity of a large collection of loads to provide VES has a complex dependency on these local quality of service constraints. Apart from MW/MWh numbers, grid operators also need to determine what kind of demand deviation is feasible for a collection of loads so that no one has to violate its local constraints. For instance, the indoor temperature should not become too hot or cold when an air conditioner is providing demand side service. These challenges are addressed in two distinct time scales: short term planning (in hours) and long-term planning (in months). For short term planning, a deterministic framework is proposed in which feasible demand trajectories are described via a set of low dimensional constraints. A key innovation is to reduce high-dimensional integer constraints due to lock-out constraints at loads into low-dimensional convex constraints for the collection through ensemble averages. For long term planning, a statistical framework based on spectral densities is proposed, which enables characterizing all possible samples paths of feasible demand deviation signals.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.