Smart Heat: Aggregating renewable-electric-heating-thermal-storage systems for grid services

我们研究的总体目标是测试一个假设，即具有先进控制的智能供热系统的聚合人口可以提供高质量的电网服务，同时保持热舒适性。智能加热系统被定义为可控的、高效的电加热设备（例如，热泵）与热存储。拟议工作的社会背景是，40%的美国人口生活在需要密集空间供暖的地区，而绝大多数空间供暖依赖于化石燃料。可再生电力驱动的供暖系统可以作为一种可持续的解决方案。然而，电加热系统的大量普及将对电力系统产生严重影响，例如高峰需求增加。研究团队将创建智能热聚集的分层控制架构，并通过演示智能热聚集的可行性来测试假设。该研究团队将与当地的几个项目合作，利用高保真和降阶建模技术以及真实社区能源系统监控，创建一个智能家居虚拟测试平台。智力优势：我们预计，我们的研究将产生一个新的控制平台，可以显式优化加热控制，以保持热舒适性并提供电网服务。提出的分层控制架构和模型预测控制负荷（MPCL）的概念将推进我们在随机优化的基本理解，也将联合智能电网和智能建筑研究社区。更广泛的影响：这项研究的结果将提高公众对两个重要问题的认识，即，可再生能源与电加热在减轻气候变化影响方面的联系，以及可再生热量中的蓄热价值。研究团队将与社区组织密切合作，通过社区会议，通讯，网站和社交媒体与公众沟通研究结果。与电动汽车一起，智能供暖概念有可能改变和统一我们围绕电力的能源系统。紧密结合的教育计划将使更多的代表性不足的少数民族（URM）学生进入可持续能源系统领域，建立在PI以前成功招募和指导URM学生的基础上。

The overall objective of our study is to test the hypothesis that an aggregated population of smart-heat systems with advanced control can provide high quality grid services while maintaining thermal comfort. Smart-heat systems are defined as controllable, efficient electric heating equipment (e.g., heat pumps) with thermal storage. The social context of the proposed work is that 40% of the US population live in regions requiring intensive space heating, and vast majority of the space heating relies on fossil fuels. Renewable electricity-driven heating systems can potentially serve as a sustainable solution. However, large penetration of electric heating systems will have severe impacts on the power systems such as elevated peak demand. The research team will create a hierarchal control architecture for smart-heat aggregation, and test the hypothesis by demonstrating the feasibility of smart-heat aggregation. In collaboration with several local initiatives, the research team will create a smart-home virtual testbed, taking advantage of high-fidelity and reduced-order modeling techniques and real-world community energy systems monitoring.Intellectual Merit: We foresee that our research will result in a new control platform to explicitly optimize heating control to maintain thermal comfort and provide grid services. The proposed hierarchal control architecture and model-predictively-controlled load (MPCL) concept will advance our fundamental understanding in stochastic optimization, and will also unite smart grid and smart building research communities. Broader Impacts: The results from this study will raise public awareness of two important issues, i.e., the linkage of renewable energy with electric heating in mitigating the impacts of climate change, and the values of thermal storage in renewable heat. The research team will work closely with community organizations to communicate the research findings with general public through community meetings, newsletters, websites, and social media. Together with electric vehicles, the smart-heat concept has the potential to transform and unify our energy systems around electricity. The closely integrated education plan will bring more under-representative minority (URM) students into the fields of sustainable energy systems, built on PI's previous success in recruiting and mentoring URM students.