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.

对于美国大多数电力市场来说，发电的边际成本和碳排放强度呈现相反的日变化趋势：在用电高峰时段，电价较高，而碳边际排放率较低，因为运营成本高但污染少。天然气“峰值”工厂对相互冲突的价格和排放信号的反应可能截然不同。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。将建立一个利他博弈理论框架，用于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部分能源消费者。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总和的利他实体。权重因子表征了个人对与能源相关的碳排放的评估，进而影响他们的能源使用。客户行为模型将根据通过以下方式收集的数据开发：（1）使用定制设计的需求响应游戏进行在线人类受试者测试，以及（2）在俄克拉荷马城市中心历史悠久的非裔美国人社区内的多户公寓大楼中进行社会技术实验。项目目标包括：(1) 生成有关住宅客户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；(2) 开发统计行为模型，描述气候利他主义与社会人口变量之间的关系。 (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，以促进行为异质性对电网财务和环境绩效的影响分析；以及（5）分布式和隐私设计；保留纳什均衡解算法以适应电力市场中灵活负载控制的分布式决策，该项目旨在通过一系列相互关联的研究、教育和推广控制策略来提高公众对负载灵活性和相关环境影响的认识。释放住宅的灵活性博弈论框架通过社会经济见解支持需求方碳减排技术、计划和政策的设计和评估。现场实验将直接吸引俄克拉荷马城提供技术的 50 户家庭，间接影响 300 多个家庭。通过与社区、开发人员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，其结果具有潜在的可扩展性和适用性。住宅领域的国家级水平。教育计划的发展，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，让他们获得跨学科技能，这对于应对未来的工程挑战至关重要。该项目由 CBET 环境可持续发展计划和制定刺激竞争性研究计划 (EPSCoR)。该奖项反映了 NSF 的法定使命，并通过使用基金会的智力价值和更广泛的影响审查标准进行评估，被认为值得支持。