EAGER: Causal Theory of Residential Electricity Consumption and Production: Unveiling Full Scale Demand Side Flexibility

EAGER：住宅电力消费和生产的因果理论：揭示全面的需求侧灵活性

• 批准号: 2225626
• 负责人: Mojdeh Hedman
• 金额: $ 19.78万
• 依托单位: Arizona State University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2022
• 资助国家: 美国
• 起止时间: 2022-09-01 至 2024-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2225626&HistoricalAwards=false
• 关键词: EAGER; Causal; Theory; Residential; Electricity

This NSF project aims to enhance residents’ interactions with smart energy systems and empower all to benefit from new opportunities of smart electric grids. Distributed energy resources, e.g., rooftop solar photovoltaic (PV) systems and flexible demand-side assets, such as smart thermostats, provide new opportunities for residents. Unlike conventional power system resources, many emerging smart energy technologies are located at the residents’ premises and their level of participation depends on many human-related factors. This NSF project proposes novel strategies to discover and account for critical underlying human-in-the-loop factors of distributed energy resources. The project will bring transformative change by enabling socially-aware design and operation of smart grid resources, which provides a wide range of financial and energy resilience benefits to residents. Understanding causality of resident behavior towards smart energy systems enables more effective design of customer programs for electric utilities, enhances retail electricity market design, and empowers more effective utilization of all distributed energy resources. This knowledge will be achieved by causal learning and analysis of consumer participation in smart grid operations. The intellectual merits of the project include design of innovative approaches to enable capturing critical components of residents’ behavior towards energy resources and their participation in energy system balancing. The broader impacts of the project include enabling effective utilization of all grid edge resources. By taking a holistic approach, which explicitly considers the interplay of social, behavioral, technological, and engineering aspects, the outcomes of this research will span multiple academic disciplines.The design of socially-aware and behavior-aware smart grid solutions is the critical step to achieve dependable and widespread participation of diverse residents in smart grid practices leading to maximum utilization of distributed energy resources. The proposed project will pursue innovative methods based on artificial intelligence algorithms for causal analysis of residents’ behavior towards emerging smart energy systems. The complex nature of human interactions with energy relies on many factors and understanding behavior causality is a core and unsolved challenge. This project makes meaningful inroads towards establishing the next generation of power systems operational strategies by enabling better utilization of all resources.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.

该NSF项目旨在增强居民与智能能源系统的互动，并赋予所有人从智能电网的新机会中受益。分布式能源资源，例如屋顶太阳能光伏（PV）系统和灵活的需求侧资产，例如智能恒温器，为居民提供了新的机会。与传统的电力系统资源不同，许多新兴的智能能源技术都位于居民的前提下，他们的参与水平取决于许多与人有关的因素。这项NSF项目提案采取了新的策略，以发现和解释分布式能源的关键基础人类因素。该项目将通过启用社会意识的设计和智能电网资源的操作来带来变革，从而为居民提供了广泛的财务和能源弹性优势。了解居民对智能能源系统行为的因果关系，可以更有效地设计用于电力的客户计划，增强零售电力市场设计，并使所有分布式能源的利用更有效地利用。通过因果学习和对消费者参与智能电网操作的分析，将实现这些知识。该项目的智力优点包括设计创新的方法，以捕获居民行为对能源资源的关键组成部分及其参与能源系统的平衡。该项目的广播公司的影响包括有效利用所有网格边缘资源。通过采取一种整体方法，该方法明确考虑了社会，行为，技术和工程方面的相互作用，这项研究的成果将涵盖多个学术学科。社会意识和行为意识的智能网格解决方案的设计是实现可靠和广泛参与智能电网实践的可靠和广泛参与最高能源的重要步骤。拟议的项目将基于人工智能算法采用创新方法，以对居民对新兴智能能源系统的行为进行灾难性分析。人类与能量相互作用的复杂性质取决于许多因素和理解行为热量是一个核心且未解决的挑战。该项目通过更好地利用所有资源来建立下一代电力系统运营策略的有意义的进攻。该奖项反映了NSF的法定任务，并通过使用基金会的知识分子和更广泛的影响审查标准来评估，被认为是宝贵的支持。