SBIR Phase II: Estimating, Learning, and Optimizing Real-Time Grid Emissions

SBIR 第二阶段：估计、学习和优化实时电网排放

• 批准号: 2051953
• 负责人: Wenbo Shi
• 金额: $ 100万
• 依托单位: SINGULARITY ENERGY, INC.
• 依托单位国家: 美国
• 项目类别: Cooperative Agreement
• 财政年份: 2022
• 资助国家: 美国
• 起止时间: 2022-03-01 至 2024-02-29
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2051953&HistoricalAwards=false
• 关键词: SBIR; Phase; II; Estimating; Learning

The broader impact/commercial potential of this Small Business Innovation Research (SBIR) Phase II project is to advance energy sustainability, especially regarding estimation, understanding, and optimization of real-time grid carbon emissions. Decarbonizing the grid means reducing its carbon emissions by decreasing the emissions per unit of electricity generated. In-depth, accurate knowledge of real-time grid emissions will facilitate various grid decarbonization use cases and applications ranging from corporate carbon accounting, carbon-aware energy management, and new emission tracking standards to future electricity and carbon market design. More broadly, the prposed platform may demonstrate that achieving near-optimal carbon emissions reductions via co-optimization for costs and carbon is possible and provide a commercially viable, scalable path for policy makers, regulators, and corporations to meet their ambitious sustainability commitments.This Small Business Innovation Research (SBIR) Phase II project seeks to develop novel and practical approaches to estimate, learn, and optimize real-time grid emissions. The Phase II project will optimize carbon estimation and forecast models, develop decision-making algorithms, implement the proposed methods as software, and validate the software platform through pilots. The team seeks to will build a user-friendly, cloud-based software platform with multiple applications that will enable climate regulators and sustainability directors to meet their public commitments and stay compliant with new regulations. Integrating real-time carbon emissions with energy and sustainability management is a critical challenge. Little is known about real-time carbon signals from the grid and the proposed project aims to demystify grid emissions to enable accurate, actionable, and transparent carbon tracking, reporting, and management.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.

这个小企业创新研究（SBIR）第二阶段项目的更广泛的影响/商业潜力是促进能源可持续性，特别是在估计，理解和优化实时电网碳排放方面。电网脱碳意味着通过减少每单位发电量的排放来减少碳排放。对实时电网排放的深入、准确的了解将促进各种电网脱碳用例和应用，从企业碳核算、碳意识能源管理、新的排放跟踪标准到未来的电力和碳市场设计。更广泛地说，该平台可以证明，通过成本和碳的共同优化实现接近最佳的碳减排是可能的，并为政策制定者，监管机构和企业提供了一个商业上可行的，可扩展的路径，以实现其雄心勃勃的可持续发展承诺。并优化实时电网排放。第二阶段项目将优化碳估算和预测模型，开发决策算法，将拟议方法作为软件实施，并通过试点验证软件平台。该团队旨在建立一个用户友好的、基于云的软件平台，其中包含多个应用程序，使气候监管机构和可持续发展主管能够履行其公开承诺，并遵守新的法规。将实时碳排放与能源和可持续性管理相结合是一项重大挑战。该项目旨在揭开电网排放的神秘面纱，实现准确、可操作和透明的碳跟踪、报告和管理。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。