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

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.