CAREER: CAS- Climate: An altruistic game theoretic framework to characterize environmental responsiveness of residential electricity consumption

对于美国的大多数电力市场来说，发电的边际成本和碳排放强度呈现出相反的日趋势：在需求高峰期，由于成本高昂但污染较少的天然气“peaker”工厂的运营，电价较高，而碳边际排放率较低。能源消费者对相互冲突的价格和排放信号的反应可能会截然不同。了解能源使用中的行为异质性及其对电力基础设施可持续性的影响，对于加快全球能源系统的脱碳至关重要。该项目将建立一个利他主义博弈论框架，以了解个人的财务和环境目标在塑造其能源使用行为方面的相互作用，并评估行为异质性对电网系统级性能的影响。利他博弈框架将每个能源消费者建模为一个部分利他的实体，其感知成本是其直接电力成本和与能源相关的碳排放的社会成本的加权和。权重系数表征了个人对与能源相关的碳排放的评估，这反过来又影响了他们的能源使用行为。客户行为模型将通过(1)使用定制设计的需求响应游戏进行在线人类主体测试和(2)在俄克拉荷马市中心一个历史悠久的非裔美国人社区内的多户公寓楼进行社会技术实验来开发。项目目标包括：(1)生成关于住宅客户对与能源相关的碳排放的评估及其对能源使用行为的影响的新知识；(2)开发一个统计行为模型，该模型表征气候利他主义如何与社会人口变量相关；(3)合成基于学习的模型预测控制策略，以实现自动需求响应；(4)建立利他博弈论框架，以便于分析行为异质性对电网财务和环境性能的影响；(5)设计分布式和隐私保护的纳什均衡解算法，以适应电力市场中灵活负荷控制的分布式决策。该项目旨在通过一系列相互关联的研究、教育和推广活动，提高公众对负荷灵活性及其对环境影响的认识。数据驱动的预测控制策略旨在通过技术发展释放住宅的灵活性潜力，而博弈论框架支持具有社会经济洞察力的需求侧碳减排技术、计划和政策的设计和评估。实地试验将直接影响俄克拉荷马城的50个家庭，并间接影响到300多个家庭，为通常不参与技术采用早期阶段的人口提供技术解决方案并对其进行教育。通过与社区、开发商和其他合作伙伴的合作，该项目将展示影响大型基础设施系统的社会驱动因素，其结果可能是可扩展的，并适用于住宅部门的国家层面。通过教育项目的发展，该项目将为K-12、代表性不足的学生、本科生和研究生提供机会，以获得对应对未来的工程挑战至关重要的跨学科技能。该项目由CBET环境可持续发展项目和既定的激励竞争研究计划(EPSCoR)共同资助。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。

For most electricity markets in the U.S., the marginal cost and carbon emission intensity of electricity generation exhibit opposite diurnal trends: during peak demand hours, the electricity price is high while the carbon marginal emission rate is low due to the operation of costly but less polluting natural gas “peaker” plants. Energy consumers may respond to the conflicting price and emission signals quite differently. Understanding the behavioral heterogeneity in energy use and its impact on sustainability of the electrical infrastructure is of critical importance to accelerating global energy system decarbonization. This project will establish an altruistic game theoretic framework to understand the interplay of an individual’s financial and environmental goals in shaping their energy use behaviors and to evaluate the impact of behavioral heterogeneity on system-level performances of the electric grid. The altruistic game framework models each energy consumer as a partially altruistic entity whose perceived cost is a weighted sum of his/her direct electricity cost and the social cost of energy-related carbon emission. The weighting factor characterizes an individual’s valuation of energy-related carbon emission, which in turn influences their energy use behaviors. Customer behavioral models will be developed from data collected through (1) online human subject tests with a custom designed demand response game and (2) sociotechnical experiments in a multi-family apartment complex within a historic African American community in downtown Oklahoma City.Project goals include: (1) generation of new knowledge on residential customers’ valuation of energy-related carbon emission and its impact on energy use behaviors; (2) development of a statistical behavioral model that characterizes how climate altruism correlates with socio-demographic variables; (3) synthesis of learning-based model predictive control strategies to enable automated demand response; (4) establishment of an altruistic game theoretic framework to facilitate impact analysis of behavioral heterogeneity on financial and environmental performances of the electric grid; and (5) design of distributed and privacy-preserving Nash equilibrium solution algorithms to accommodate distributed decision making for flexible load control in electricity markets. The project aims to increase public awareness of load flexibility and the associated environmental impact through a series of interrelated research, educational and outreach activities. The data-driven predictive control strategies are designed to unlock the residential flexibility potential through technological development, while the game theoretic framework supports design and assessment of demand-side carbon reduction technologies, programs and policies with socio-economic insights. The field experiment will directly engage 50 and indirectly affect more than 300 households in Oklahoma City providing technology solutions to and educating a population that does not usually engage in the early stages of technology adoption. Through collaboration with the community, developers and other partners, the project will demonstrate social drivers that affect large infrastructure systems, with the results potentially scalable and applicable on a national level in the residential sector. Through the education program development, this project will provide opportunities for K-12, underrepresented, undergraduate, and graduate students to acquire cross-disciplinary skills that are critical to addressing future engineering challenges.This project is jointly funded by the CBET Environmental Sustainability program and the Established Program to Stimulate Competitive Research (EPSCoR).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.