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

该NSF项目旨在经验性地检验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)而导致的不同类型的电力消耗和技术使用行为变化。了解不同的共同采用者行为对于公用事业公司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非常重要。该项目将给电力系统的理解和仿真带来革命性的变化，因为共同采用这些技术的消费者的普及率越来越高。这将通过使用大规模、多年、高频的个人消费者级别的智能电表数据，并结合包含高级数据分析、计量经济学、机器学习和模拟方法的跨学科方法来实现。该项目的智力优势包括1)开发因果框架，通过该框架，我们提供共同采用对消费者行为的影响的经验估计，并检查关税和技术、家庭和家庭的可观察特征如何影响变化；2)揭示行为异质性，并将每个人的行为变化归类为理性、非理性、错误信息或环境驱动的行为；3)开发第一个经验证的建筑物到电网的集成框架，从而能够评估新能源技术共同采用的影响。该项目的更广泛影响包括促进采用PV、电动汽车和电池存储技术，通过将工程与经验行为分析相结合来转变相关的工程建模，以及吸引行业从业者，他们的决策将得到项目产品的帮助。现有的理解这些技术的共同采用者的用电行为的模型主要是基于工程的，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预测的行为，而且这种偏离可能是不同的。此外，共同采用者的行为变化不仅仅是对个别技术采用所带来的变化的简单总结，因为一种技术的使用可能会因为共同采用另一种技术而发生变化。该项目通过对能源技术共同采用的不同影响提供首创的经验评估，以及通过纳入经验共同采用者的行为来推进现有建筑到电网的建模，填补了这些主要空白。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 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.