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

职业：CAS-气候：描述住宅用电环境响应的利他博弈理论框架

• 批准号: 2238381
• 负责人: Jie Cai
• 金额: $ 50.8万
• 依托单位: University of Oklahoma Norman Campus
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 2023
• 资助国家: 美国
• 起止时间: 2023-02-15 至 2028-01-31
• 项目状态: 未结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2238381&HistoricalAwards=false
• 关键词: CAREER; CAS; Climate; altruistic; game

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.

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：在用电高峰时段，电价高，而碳边际排放率低，这是由于运行成本高但污染较小的天然气“调峰”电厂。能源消费者可能会对相互冲突的价格和排放信号做出完全不同的反应。了解能源使用的行为异质性及其对电力基础设施可持续性的影响，对于加速全球能源系统脱碳至关重要。本研究将建立一个利他博弈理论框架，以了解个人的财务和环境目标在塑造其能源使用行为中的相互作用，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视为一个部分利他的实体，其感知成本是他/她的直接电力成本和能源相关的碳排放的社会成本的加权和。权重因子表征了个体对与能源相关的碳排放的评价，进而影响其能源使用行为。客户行为模型将根据收集的数据开发，这些数据是通过（1）使用定制设计的需求响应游戏进行的在线人类受试者测试，以及（2）在俄克拉荷马州市中心一个历史悠久的非裔美国人社区内的多户公寓大楼中进行的社会技术实验。项目目标包括：（1）关于居民消费者对能源相关碳排放的评估及其对能源使用行为的影响的新知识的产生;（2）开发一个统计行为模型，描述气候利他主义如何与社会人口变量相关;（3）综合基于学习的模型预测控制策略，以实现自动需求响应;（四个）建立一个利他博弈理论框架，以便于分析行为异质性对财务和环境绩效的影响电网;（5）设计分布式隐私保护Nash均衡求解算法，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、教育和外联活动，提高公众对负荷灵活性和相关环境影响的认识。数据驱动的预测控制策略旨在通过技术发展释放住宅灵活性潜力，而博弈论框架支持设计和评估需求方的碳减排技术，计划和政策，并具有社会经济见解。现场实验将直接参与俄克拉荷马州的50个家庭，间接影响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和教育。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，其结果可能在国家一级的住宅部门中扩展和适用。通过教育计划的发展，该项目将为K-12，代表性不足，本科生，该项目由CBET环境可持续发展计划和刺激竞争力研究的既定计划（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。