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。新冠肺炎疫情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电力支出增长。对这些群体可能造成的不公平的能源影响可能是由于能效较低的家庭、对电器（即学校电脑）的需求增加以及家庭规模较大。由此造成的更高的能量消耗负担可能意味着这些群体在创造舒适的室内环境方面受到限制，而这对于在大流行期间保持良好健康尤为重要。本项目将(1)量化电力支出再分配，并揭示随着裁员增加，这与财富再分配的关系；(2)深入了解疫情对不同消费者类型电网的影响。这项工作将为能够减轻最弱势群体能源负担的政策提供信息，这些群体的工作保障、教育发展和心理健康与他们满足能源需求的能力息息相关，特别是在国际危机期间。为了进行这项研究，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每小时智能电表用电需求数据的大量样本，以及纽约市的电力和供暖天然气消费数据，进行消费者级统计和机器学习分析。这将与住宅消费者的详细社会人口统计和建筑属性信息相结合，从而可以更详细地分析电力影响和对能源支出的影响。我们还将开展消费者调查，调查因疫情导致的用电行为变化。这场大流行病还突出表明，有必要改进对能源不平等和贫困的衡量。我们将根据能源消费水平的距离建立一个指数来衡量家庭无法获得足够的能源服务。这个指数一旦开发出来，就可以被公用事业和政策制定者用来及时、准确地识别遭受能源贫困的消费者。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告知公用事业公司，哪些类型的需求侧管理实践（如分时定价）可以帮助或伤害遭受能源贫困的消费者。对负荷概况的消费者级分析将提供异构影响估计，因此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出现长期结构性变化，因此在病毒消失后，负荷曲线可能不会反弹回原来的模式。最后，我们的消费者层面分析将量化危机导致的温度响应函数的异质变化（消费者如何根据温度变化改变其用电量）。量化这种复杂的电力需求再分配对负荷形状的影响，将有助于公用事业公司更好地规划容量和投资组合管理。如果冠状病毒在整个夏季冷却负荷高或可能出现更多冠状病毒时持续存在，这一点尤为重要。该奖项反映了美国国家科学基金会的法定使命，并通过使用基金会的知识价值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.