About the Event
The electric power system is currently in its biggest transition since its inception. An important part of this transition is to significantly increase the amount of renewable generation. Ambitious goals of up to 30% renewable generation by 2030 have been set. Wind generation is the fastest growing renewable generation source. But this generation resource is variable and intermittent, i.e. not continuously available and not at times most needed. This talk concentrates on how predictive control can be used to make optimal usage of existing and minimizing the need for additional balancing resources for the integration of a significant amount of wind generation. In particular, we investigate the potential of storage devices and run-of river power plants in a generation/storage dispatch including environmental impacts as costs. Storage devices are the perfect match for variable generation resources and their optimal usage will reduce emissions from conventional generation and open the door for slow ramping generation plants to act as backup generation. On the other hand, changing the role of run-of river power plants from base load power plants to variable resources provides another source for balancing the variability of wind generation. This includes using fluid dynamics to predict and optimally schedule available hydro power. Hence, this research gives an indication of the potential of storage devices and hydro power for the integration of renewable generation.
Gabriela Hug is an Assistant Professor with the Department of Electrical and Computer Engineering at Carnegie Mellon University. She received her M.Sc. degree in Electrical Engineering and her PhD degree in Electric Power Systems from the Swiss Federal Institute of Technology (ETH) Zurich in 2004 and 2008, respectively. In 2008 - 2009, she was with the Special Studies Group of Hydro One, Toronto, Canada, which is responsible for the transmission system of Ontario. She joined Carnegie Mellon University in July 2009.
She is the recipient of the ETH medal and the ETG Innovation Award for her M.Sc. thesis and the ABB research award for her PhD thesis.
Her research focuses on optimization and control in electric power systems, the integration of intermittent renewable generation, Flexible AC Transmission Systems (FACTS), application of predictive control and decomposition theory in the electric power system.