CAREER: Energy Storage Systems for Dynamic Reliability of Modern Clean Smart Grid

NSF CAREER项目旨在建立先进的储能系统管理策略，以确保其有效运行，并在动态电力市场中提高系统的稳定性和可靠性。该项目将带来数学和控制框架和方法的变革，以解决现代电力系统中日益增加的分布式随机组件和复杂通信层的挑战。这将通过开发改进的模型来实现，这些模型将充分反映智能电网中ess的动态、通信、协调和贡献。该项目的智力优势包括在动态网络物理系统的背景下建立运行和管理ess的科学和工程原理，以确保电网的安全和经济，并制定教育计划，为未来几代工程师提供操作和推进现代系统的专业知识。该项目的广泛影响超出了其研究目标。该项目通过提高美国电网的稳定性、公平性、可靠性和环境可持续性，有助于推进美国的能源安全。它还通过促进能源部门的增长来促进国家经济。该项目还致力于社会责任和包容性，促进能源和技术劳动力的多样化。该项目有望产生重大的教育影响，包括新课程的开发，研究生和本科生研究项目的加强，以及创造新的指导和职业机会，特别是对于那些来自STEM中代表性不足的群体的人。该项目的动机是，尽管具有环境优势，但可再生能源和电动汽车的快速整合对电力系统的稳定性和可靠性提出了重大挑战。虽然这些挑战可以通过储能系统来解决，但它们的发展仍处于早期阶段，没有建立标准或管理体系。该项目的目标是：1)确定储能系统的关键因素，建立储能系统的动态稳定性模型，优化管理，以支持大规模可再生能源和电动汽车；Ii)使用先进的机器学习技术开发监管市场中集成系统的复合可靠性模型。本研究成果将有助于基础可靠性评估和能源管理方法的发展，并提供可应用于不同研究领域的解决算法。该项目将对智能清洁电网的运行产生重大影响，其目标是在经济、技术、环境和社会方面具有多重优势。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。

This NSF CAREER project aims to establish advanced strategies for energy storage systems (ESSs) management to ensure their effective operation and improve system stability and reliability within dynamic electric markets. The project will bring transformative changes in mathematical and control framework and methodology that address the challenges of increasing distributed stochastic components and intricate communication layers in modern power systems. This will be achieved by the development of improved models that fully reflect the dynamics, communication, coordination, and contributions of ESSs in a smart grid. The intellectual merits of the project include the establishment of science and engineering principles for the operation and management of ESSs in the context of dynamic cyber-physical systems to ensure secure and economic power grids, and an education plan to prepare future generations of engineers with the know-how to operate and advance modern systems. The broader impacts of the project reach beyond its research objectives. The project contributes to advancing the nation's energy security by improving the stability, equity, reliability, and environmental sustainability of the U.S. power grids. It also boosts the nation's economy by fostering the growth of energy sectors. The project also commits to social responsibility and inclusivity by contributing to diversifying the energy and technology workforce. The project promises a significant educational impact, including new curriculum development, enhancement of graduate and undergraduate research programs, and the creation of new mentorship and career opportunities, particularly for those from underrepresented groups in STEM.The project is motivated by the fact that despite environmental advantages, the rapid integration of renewable energy resources and electric vehicles causes significant challenges to power system stability and reliability. Although these challenges can be tackled by energy storage systems, their evolution is still in the early stages without established standards or management systems. The goals of this project are to i) determine key factors and establish dynamic stability models of energy storage systems to optimize their management to support large-scale renewable energy resources and electric vehicles; ii) develop a composite reliability model of integrated systems in the regulatory market using advanced machine learning techniques. The outcome of this research will contribute to the advancement of fundamental reliability evaluation and energy management approaches and the provision of solution algorithms that can be applied in different research domains. The project would have significant impacts on the operation of smart clean grids with the targets of multiple economic, technical, environmental, and societal advantages.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.