RAPID: Coronavirus, new patterns in electricity demand, and energy inequality

该项目的目的是通过调查冠状病毒大流行对电力需求的影响来促进国民健康和福利。这场流行病导致了广泛的居家政策，这意味着，低收入人群、少数民族和老年人等弱势群体可能面临不成比例的更高的电力支出增长。对这些群体可能造成的不公平能源影响可能是由于家庭能效较低、对电器(如学校电脑)的需求增加以及家庭规模扩大所致。由此产生的更高的能源支出负担可能意味着限制这些群体创造舒适的室内环境，这对在大流行期间保持良好的健康尤为关键。该项目将(1)量化电力支出再分配，并揭示这与裁员增加时财富再分配的关系；(2)更深入地了解疫情对不同消费类型电网的影响。这项工作将为政策提供信息，以减轻最脆弱人群的能源负担，他们的工作保障、教育发展和心理健康与他们满足能源需求的能力有关，特别是在国际危机期间。在追求这项研究的过程中，研究团队将使用亚利桑那州凤凰城和伊利诺伊州芝加哥大都会的住宅、商业、工业和农业部门的个人消费者级别的每小时智能电表电力需求数据以及纽约市的电力和供暖天然气消费数据进行消费者级别的统计和机器学习分析。这将与住宅用户的详细社会人口和建筑属性信息结合在一起，从而能够更详细地分析电力影响和对能源支出的影响。我们还将进行一项消费者调查，研究疫情对用电行为的影响。这场流行病还突显了改进能源不平等和贫困的衡量标准的必要性。制定能源消费水平距离指数，衡量居民获得足够能源服务的能力。一旦制定了这一指数，公用事业公司和政策制定者就可以利用这一指数及时、准确地确定遭受能源贫困之苦的消费者。我们将在负荷概况的背景下研究能源贫困，以便我们的研究结果可以向公用事业公司提供信息，说明哪种类型的需求侧管理做法可以帮助或伤害遭受能源贫困困扰的消费者。对负荷分布的消费者层面的分析将提供不同的影响估计，从而可以更好地帮助公用事业公司预测未来对负荷的影响并评估不确定性。这一点尤其重要，因为需求模式可能会有长期的结构性变化，因此在病毒消失后，负载曲线可能不会反弹到原始模式。最后，我们的消费者层面的分析将量化由于危机而导致的温度响应函数(消费者如何改变其用电量)的异质性变化。量化如此复杂的电力需求重新分配对负荷形态的影响，将有助于公用事业公司更好地规划产能和投资组合管理。如果冠状病毒在整个夏季持续存在，当冷负荷很高，或有可能出现更多冠状病毒浪潮时，这一点将特别重要。这一奖项反映了NSF的法定使命，并已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 advance national health and welfare through investigating the impact of the coronavirus pandemic on electricity demand. The pandemic has resulted in widespread stay-at-home policies meaning that, vulnerable populations such as those with low income, ethnic minorities, and the elderly might face a disproportionally higher increase in electricity expenditure. The likely inequitable energy impact on these groups could be a result of less energy-efficient homes, increased need for electrical appliances (i.e. school computers), and larger household sizes. The resulting higher energy expenditure burden might imply constraints of these groups to create a comfortable indoor environment, which is particularly vital to maintaining good health during a pandemic. This project will (1) quantify the electricity expenditure re-distribution and uncover how this relates to the wealth redistribution as lay-offs increase; (2) develop a deeper understanding of the pandemic's impact on the electricity grid for different consumer types. This work will inform policies that can reduce the energy burden of the most vulnerable populations whose job security, educational development, and mental health are linked to their ability to satisfy their energy demand, particularly during an international crisis.In pursuit of this research the research team will conduct consumer-level statistical and machine learning analyses using large samples of individual-consumer-level hourly smart meter electricity demand data in the residential, commercial, industrial, and agricultural sectors in Phoenix metropolitan, Arizona, and Chicago metropolitan, Illinois, as well as electricity and heating gas consumption data in New York City, New York. This will be combined with detailed socio-demographic and building attribute information for residential consumers which will allow for a more detailed analysis of electricity impacts, and impacts on energy expenditure. We will also conduct a consumer survey examining the changes in electricity consumption behaviors due to the pandemic. The pandemic has also highlighted the need to improve the measurement of energy inequality and poverty. We will develop an index based on the distance in energy consumption levels to measure the inability of households to obtain sufficient energy services. Once developed this index can then be used by the utilities and policymakers to identify the consumers suffering from energy poverty in a timely and precise fashion. We will examine energy poverty in the context of load profiles so that our findings can inform utilities regarding what types of demand-side management practices such as time-of-use pricing can help or hurt the consumers suffering from energy poverty. The consumer-level analysis on the load profiles will provide heterogeneous impact estimates and thus can better help utilities forecast future impacts on load and evaluate the uncertainties. This is especially important because there might be long-term structural changes in the demand patterns so that the load curves may not rebound back to the original patterns when the virus is gone. Lastly, our consumer-level analysis will quantify the heterogeneous changes in the temperature-response functions (how consumers change their electricity consumption in response to temperature change) due to the crisis. Quantifying the impact of such a complex redistribution of electricity demand on the load shape will help utilities better plan for capacity and portfolio management. This will be particularly important if coronavirus is persistent throughout the summer when cooling loads are high, or when there is a possibility of more waves of coronavirus.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.