ECCS-EPCN: Stochastic Power Control and Learning for Energy Grids

这个项目研究了一个计算框架来处理即将到来的电力系统的随机、动态和时空分布性质。设想在适应性、意识和可扩展性方面的进步旨在吸引目前不活跃的电力消费者参与可持续电力系统。光伏、风能、储能系统和电动汽车的顺利整合，将促进创新和发展，显著推进资源配置、学习和监测基础设施。拟议的研究旨在促进能源网络的广泛社会技术进步。该项目的成功完成将提供网络创新，以实现随机可再生能源发电的系统集成，同时提高最终用户满意度。鉴于研究工具和方法的通用性，拟议研究的实用性远远超出了预期的应用领域，涉及更广泛的领域，如优化、随机过程、控制系统、机器学习、统计信号处理和网络安全。更广泛的变革影响将来自为验证而提出的实用测试用例、本科生参与研究和拓展活动。

This project investigates a computational framework to deal with the stochastic, dynamic, and spatio-temporally distributed nature of forthcoming power systems. The envisioned advances in adaptivity, awareness, and scalability aim at engaging currently inactive electricity consumers in a sustainable power system. Smooth integration of photovoltaics, wind, storage systems, and electric vehicles, will promote innovation and development, in terms of markedly advancing the resource allocation, learning, and monitoring infrastructure. The proposed research aims for broad socio-technical advances in energy networks. Successful completion of the project will offer cyber innovations to enable systematic integration of stochastic renewable generation while improving end-user satisfaction. Given the universality of the research tools and methodologies, the utility of the proposed research goes well beyond the envisioned application area to the broader fields of optimization, stochastic processes, control systems, machine learning, statistical signal processing, and cyber security. Broader transformative impact will result from pragmatic test cases proposed for validation, involvement of undergraduates in research, and outreach activities.