Collaborative Research: Empirical assessment of the heterogeneous changes in electricity consumption behaviors due to co-adopting batteries, electric vehicles, and solar panels

该NSF项目旨在实证研究由于住宅消费者共同采用分布式太阳能电池板（PV），电池存储和电动汽车（EV）而导致的异构电力消耗和技术使用行为变化。了解异质共同采用者的行为是重要的公用事业和政策制定者采取更有针对性的干预措施，以诱导需求侧管理所需的行为变化。该项目将为电力系统的理解和模拟带来变革性的变化，并增加共同采用这些技术的消费者的渗透率。这将通过使用大规模，多年，高频率的个人消费者级智能电表数据，结合包括先进的数据分析，计量经济学，机器学习和模拟方法的跨学科方法来实现。 该项目的智力价值包括：1）开发一个因果框架，通过该框架，我们提供了共同采用对消费者行为影响的经验估计，并研究了关税和技术，住宅和家庭的可观察特征如何影响变化; 2）揭示行为异质性，并将每个个体的行为变化分为理性、非理性、误导，或环境驱动的行为; 3）开发第一个经过验证的建筑物到电网集成框架，可以评估新能源技术共同采用的影响。该项目更广泛的影响包括促进PV、EV和电池存储技术的采用，通过将工程与经验行为分析相结合来改造相关的工程建模，以及吸引行业从业者，他们的决策将得到该项目产品的帮助。现有的模型来了解这些技术的共同采用者的电力消费行为主要是基于工程的，并没有考虑到实际的消费者行为和相关的异质性。然而，消费者的实际行为可能会偏离工程模型的预测，这种偏离可能是异质的。此外，共同采用者的行为变化不仅仅是由于个别技术采用而引起的变化的简单总和，因为一种技术的使用可以由于共同采用另一种技术而发生变化。该项目填补了这些主要空白，提供了能源技术共同采用的异质性影响的首个经验评估，并通过纳入经验共同采用者的行为来推进现有建筑物到电网的建模。该奖项反映了NSF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。

This NSF project aims to examine empirically the heterogeneous electricity consumption and technology-using behavioral changes due to the co-adoption of distributed solar panels (PVs), battery storage, and electric vehicles (EVs) of residential consumers. Understanding the heterogeneous co-adopter behaviors is important for utilities and policymakers to adopt better-targeted interventions to induce behavioral changes needed for demand-side management. The project will bring transformative change to the understanding and simulation of the power systems with increasing penetration of consumers that co-adopt these technologies. This will be achieved by using a large scale, multi-year, high frequency individual-consumer-level smart meter data, combined with an interdisciplinary approach encompassing advanced data analytics, econometrics, machine learning, and simulation methods. The intellectual merits of the project include 1) developing a causal framework, through which we provide the empirical estimates of the impact of co-adoption on consumer behaviors, as well as examine how changes are affected by tariffs and observable characteristics of technologies, homes, and households; 2) uncovering the behavioral heterogeneity and categorizing each individual’s behavior changes into rational, irrational, misinformed, or environmental-driven behaviors; 3) developing the first empirically-validated buildings-to-grid integration framework that enables evaluation of the impacts of new energy technology co-adoption. The broader impacts of the project include facilitating the adoption of PVs, EVs, and battery storage technologies, transforming relevant engineering modeling by combining engineering with empirical behavioral analysis, and engaging industry practitioners, whose decision-making will be assisted by the project’s products. Existing models to understand the electricity consumption behaviors of co-adopters of these technologies are largely engineering-based and do not account for actual consumer behaviors and the related heterogeneity. However, consumers’ actual behaviors can deviate from those predicted by engineering models and such deviations can be heterogeneous. Also, co-adopters’ behavior changes are not just a simple summation of the changes due to individual technology adoption, because the usage of one technology can change due to co-adopting another technology. This project fills these major gaps by providing a first-of-a-kind empirical assessment of the heterogeneous impacts of energy technology co-adoption as well as by advancing existing buildings-to-grid modeling through incorporating empirical co-adopters’ behaviors.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.