CAREER: Data-driven dynamic adaptive optimization for next generation power system operation

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The objective of this Faculty Early Career Development Program (CAREER) project is to create a set of novel optimization models and algorithms for the operation of future electric power systems. The approach is to (1) develop efficient and robust algorithms for optimizing power flow and power network topology, which will be significantly faster, more accurate, and more scalable than the state-of-the-art approaches; (2) develop new techniques for harnessing large amount of data for modeling uncertainties in power system; (3) develop decision making algorithms for the real-time operation of power systems with substantial renewable, demand response, and distributed generation resources. The intellectual merits of the project lie in (1) the development of new insights and understanding of some key mathematical structures of a broad class of hard optimization problems involving networks, which are intrinsic to optimal power flow, network topology control, and dynamic decision making, and (2) leveraging these mathematical understanding to design rigorous and efficient algorithms for the mentioned problems. If successful, this research will not only provide transformative technologies for the operations of power grid, but will also strengthen intellectual ties between power engineering and industrial & operations engineering. The project will directly benefit the society at large by creating the next generation of operational tools to manage the future power grids, to help reduce power system operational cost, and to increase power system reliability and flexibility. The methodological contributions of the project will provide new tools for applications beyond electric power systems, such as for the operation of water and natural-gas networks and coordination of interconnected energy systems. The PI will actively pursue opportunities to bring power industry, academia, government, and national labs together to form synergistic discussions and collaborations on developing analytical methods for electric energy systems. The PI will also develop new education curriculum and outreach activities to contribute to the development of a new generation of multidisciplinary workforce for the nation's infrastructure industry.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.