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

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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.