SBIR Phase I: Estimating, Learning, and Optimizing Real-Time Carbon Emissions for Energy and Sustainability Management

SBIR 第一阶段：估算、学习和优化实时碳排放，以实现能源和可持续发展管理

• 批准号: 1938082
• 负责人: Wenbo Shi
• 金额: $ 22.5万
• 依托单位: SINGULARITY ENERGY, INC.
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2019
• 资助国家: 美国
• 起止时间: 2019-12-01 至 2020-11-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1938082&HistoricalAwards=false
• 关键词: SBIR; Phase; Estimating; Learning; Optimizing

The broader impact/commercial potential of this Small Business Innovation Research project is that it will advance the area of energy sustainability with proactive monitoring and management of carbon emissions in real time. The knowledge of real-time grid carbon data will provide a new perspective for various applications ranging from smart grid controls to future electricity market design. More broadly, the demonstration of achieving near-optimal carbon emissions reduction without sacrificing economics will provide a commercially viable, scalable path to proactively manage carbon emissions under existing market mechanisms.This Small Business Innovation Research (SBIR) Phase I project will: 1) estimate real-time carbon emissions and analyze grid carbon intensity models from historical data using statistical (offline) learning approaches, 2) design real-time/online optimization and control approaches to reduce carbon emissions while maximizing economic benefits under uncertainties, and 3) develop a proof-of-concept software platform, implement the models and strategies, integrate with hardware, and validate the methods through a pilot. A major theme is to integrate real-time carbon emissions with energy and sustainability management to estimate real-time carbon emissions, develop grid carbon intensity models, leverage real-time data to improve sustainability, and make real-time control decisions under uncertainties of the ambient environment and customer 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.

这个小型企业创新研究项目的更广泛的影响/商业潜力在于，它将通过实时积极监控和管理碳排放量来推动能源可持续性领域。实时网格碳数据的知识将为从智能电网控制到未来的电力市场设计等各种应用程序提供新的视角。 更广泛地说，在不牺牲经济学的情况下实现近乎最佳的碳排放减少的演示将提供一条可行的可行，可扩展性的途径，以在现有市场机制下主动管理碳排放，这是小型企业创新研究（SBIR）I阶段I项目，I阶段I项目将：1）估算在线碳量和分析型碳强度数据（使用历史上的数据），使用碳量的模型（使用历史上的碳量化）（使用历史上的碳/分析）（使用历史上的碳量）（使用历史上的数据）（使用历史上的碳/分析）（使用历史上的数据）（优化和控制方法可以减少碳排放，同时在不确定性下最大化经济利益，以及3）开发概念验证软件平台，实施模型和策略，与硬件集成并通过飞行员验证方法。一个主要主题是将实时碳排放与能源和可持续性管理集成以估计实时碳排放，开发网格碳强度模型，利用实时数据来提高可持续性，并在不确定性的环境环境和客户行为的不确定性下做出实时控制决策，这反映了NSF的法定任务和审查的范围。