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Multi-level optimization for reliable planning and operations of power systems with renewable integration

Neng Fan, Assistant Professor, Systems and Industrial Engineering Department, University of Arizona

Reliability and sustainability are two important issues for upgrading current power system into the smart grid, with enhanced reliability standards and large portion of renewable resources integration. In this talk, we present a multi-level and large-scale optimization framework, to incorporate North American Electric Reliability Corporation reliability standards (NERC standards under N-1, N-k, N-1-1 contingencies, etc.), and to mitigate uncertainties from failures and intermittent renewables, for coordinated planning and operations of power systems. Some specific problems within this framework will be presented and numerical experiments are performed to validate the proposed models and algorithms.


Dr. Neng Fan is an assistant professor at Systems and Industrial Engineering Department, The University of Arizona (UA). He obtained his bachelor degree in mathematics from Wuhan University, in 2004, and master degree in applied mathematics from Nankai University in 2007. In 2009 and 2011, he obtained his master and PhD degrees from Industrial and Systems Engineering Department at University of Florida, respectively. Before joining UA, he worked in Los Alamos and Sandia National Laboratories from 2010 to 2012.

His research interests include integer programming, stochastic and robust programming methods, and their applications in data mining, machine learning, combinatorial optimization, energy systems, water systems and health care.