Large-Scale DER Aggregation: Active Prosumers, Optimal Aggregation, and Sustainable Growth

风能、太阳能和电池技术的突破，再加上传感、控制和人工智能等信息技术的进步，使随时随地大规模聚集小型但无处不在的可再生能源成为可能。该项目旨在开发科学原理和工程解决方案，以实现分布式能源大规模聚合的变革性创新。该项目解决了在大容量输电和分布式发电和需求资源来源的传统配电系统之间的界面上实现零碳能源生产、传输和分配的主要挑战。该项目的智力优势包括：(1)将太阳能、储能和灵活需求（如电动汽车充电和恒温控制）集成在一起的新颖随机和动态优化技术；(2)实用和数据驱动的聚合解决方案；(3)用于分析短期和长期技术采用过程和政策设计的系统理论模型。这项研究的广泛影响包括解决开发实用工程和商业模式的迫切需求，这些模式促进了小型和分布式能源的高效、有竞争力和大规模整合。这项研究的跨学科性质使工程专业的学生能够获得经济分析的工具，并深入了解工程设计的经济和社会影响。该项目为工程教育一个关键领域的课程发展提供了机会，并扩大了妇女和代表性不足的少数民族学生对电力和能源系统研究的参与。本研究的技术重点是在三个广泛的方向上推进控制、优化和机器学习的基础理论和技术：(1)具有表后代、存储和灵活需求的产消者的最优决策过程，(2)追求利润的聚合者参与批发市场的最优能源聚合策略，以及(3)大规模分布式能源聚合带来的短期和长期市场均衡、社会福利分配、公平和可持续增长的特征。从经济效率、接入公平性、计算复杂度和可扩展性等方面分析了配电系统运营商和批发市场独立系统运营商的实际聚合和协调模型。该奖项反映了美国国家科学基金会的法定使命，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。

Breakthroughs in wind, solar, and battery technologies, coupled with advances in information technology in sensing, control, and artificial intelligence, are making it possible for the large-scale aggregation of small-sized but ubiquitous renewable energy resources anytime, anywhere. This project aims to develop scientific principles and engineering solutions that enable transformative innovations in the large-scale aggregation of distributed energy resources. The project addresses major challenges in achieving zero-carbon energy generation, transmission, and distribution at the interface between the bulk transmission and the traditional distribution systems where distributed generation and demand resources originate. The intellectual merits of the project include the development of (i) novel stochastic and dynamic optimization techniques that integrate behind-the-meter solar, storage, and flexible demands such as electric vehicle charging and thermostatic control, (ii) practical and data-driven aggregation solutions, and (iii) system-theoretic models for the analysis of short and long-run technology adoption process and policy designs. The broader impacts of this research include addressing cogent needs of developing practical engineering and business models that facilitate efficient, competitive, and large-scale integrations of small-sized and distributed energy resources. The interdisciplinary nature of this research enables engineering students to gain tools of economic analysis and insights into the economic and societal impacts of engineering designs. The project provides opportunities for curriculum developments in a critical area of engineering education and broadens the participation of women and underrepresented minority students in power and energy system research.The technical thrusts of this research aim to advance fundamental theory and technology in control, optimization, and machine learning in three broad directions: (i) optimal decision processes for prosumers with behind-the-meter generations, storage, and flexible demands, (ii) optimal energy aggregation strategies for the profit-seeking aggregator to participate in the wholesale market, and (iii) characterization of short and long-run market equilibrium, social welfare distribution, equity, and sustainable growth brought by large-scale distributed energy resource aggregations. Practical aggregation and the coordination models of distribution system operators and the wholesale market independent system operators are developed and analyzed for their economic efficiency, equity of access, computation complexity, and scalability.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.