A Cross-Domain Data-driven Approach to Analyzing and Predicting the Impact of COVID-19 on the U.S. Electricity Sector

该项目旨在开发一种跨域、以数据为导向的方法，以跟踪和衡量正在进行的新冠肺炎大流行对美国电力行业的影响。新冠肺炎危机超出了任何人的想象，正在成为一场百年一遇的社会挑战。作为公民社会的命脉和关键的使能基础设施系统，电力行业正在迅速适应新常态，了解电网在应对新冠肺炎造成的中断时的严重性和弹性至关重要。该项目证实了一种以数据为导向、以科学为基础的方法，以评估各种政策选择对电力基础设施运作的影响。一旦成功实施，该项目将为电力部门提供亟需的规划决策支持。该研究项目将与培养电力和公共卫生领域未来领导者的教育努力紧密结合在一起。研究小组邀请女性和非裔美国学生参与建立这个数据中心的初步版本，并继续对该项目进行研究。该团队还与行业成员合作，为广泛的行业附属机构提供培训材料。该项目的目标是开发首个此类跨域数据中心，并对COVID对美国电力行业的影响进行数据驱动的分析。方法是1)建立一个全面的开放获取的数据中心，具有质量监测和日常更新，2)使用集合回溯模型和限制向量自回归(VAR)来量化电力消费对社会距离和公共卫生政策的敏感性，以及3)构建考虑社会距离政策和不同行业流动性的电力部门预测模型。这个项目的贡献有四个方面。首先，这是首个此类数据中心，它将电力市场、公共卫生和移动数据等原本不相关的数据领域整合到一个连贯的基础设施中。提出了一种基于机器学习的清洗和预处理技术。第二，提出了一种统计方法来量化公共卫生危机对电力部门的独特影响。这需要建立和分析新的统计模型，将社会流动性和公共卫生数据纳入美国主要热点地区的电力消费回归分析。第三，提出了电力消费相对于社会流动性的弹性概念，并将其作为作为社会疏远政策措施函数的电力消费的有效指标得到证实。最后但并非最不重要的是，该项目将结合上述三项创新，根据社会距离政策和公共卫生数据创建首个电力部门预测模型。利用生物统计学和电力工程的专业知识，该项目将有助于公共卫生和电力能源部门之间的相互促进。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。

This project aims at developing a cross-domain, data-driven approach to tracking and measuring the impact of the ongoing COVID-19 pandemic on the U.S. electricity sector. The COVID-19 crisis has gone beyond anybody’s wildest imagination and is turning out to be a once-in-a-century societal challenge. As the lifeblood of civil society and a key enabling infrastructure system, the electricity sector is quickly adjusting to the new normal, and it is crucial to understand the severity and the resiliency of the grid in response to disruption caused by COVID-19. This project substantiates a data-driven, science-based approach to evaluating the impact of various policy options on the operation of the electric energy infrastructure. Once successfully pursued, the project will provide much needed planning decision support for the electricity sector. The research program will be tightly coupled with an educational effort to train future leaders in the electricity and public health sectors. The research team has engaged female and African American students in building the preliminary version of this data hub and to continue research on the project. The team is also working with the industry members to provide training materials to a broad set of industry affiliatesThe goal of this project is to develop a first-of-its-kind cross-domain data hub and data-driven analysis of the COVID’s impact on the U.S. electricity sector. The approach is to 1) build a comprehensive open-access data hub with quality monitoring and daily updates, 2) quantify the sensitivity of electricity consumption with respect to social distancing and public health policies by using Ensemble Backcast Models and Restricted Vector Autoregression (VAR), and 3) construct a predictive model for the electricity sector considering social distancing policies and mobility in different sectors. The contribution of this project is four-fold. First, this is a first-of-its-kind data hub that combines otherwise unrelated domains of data like electricity markets, public health, and mobility data into a coherent infrastructure. A machine learning-based cleaning and pre-processing technique is proposed. Second, a statistical approach is proposed to quantify the unique impact of a public health crisis on the electricity sector. This entails building and analyzing novel statistical models that encompass societal mobility and public health data into the regression analysis of electricity consumption in major hot spots in the U.S. Third, a novel concept of elasticity of power consumption with respect to societal mobility is proposed and substantiated as an effective indicator of the power consumption as a function of social distancing policy measures. Last but not least, this project will combine all the above three innovations to create a first-of-its-kind predictive model of electricity sector as a function of social distancing policies and public health data. Drawing upon expertise from biostatistics and electric power engineering, this project will contribute to the cross-fertilization between the public health and electric energy sectors.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.