ECE Department Calendar
Dr. Alexis Kwasinski
University of Texas-Austin
When: Monday, February 3, 2014 at 3:05 p.m.
Where: Warnock 1230
This presentation analyzes system-level planning and component-level design approaches to achieve high power supply availability during and after natural disasters. It starts by explaining the motivation of this analysis with a description of photographic evidence and information collected during field damage assessments after recent notable natural disasters. This evidence seems to indicate that conventional power grids are very fragile systems due to their primarily centralized power distribution and control architectures and explains why conventional mitigation strategies and many smart grid technologies yield limited resiliency improvement. The second part of this presentation introduces microgrids as an alternative technology that does not have these limitations. A system-level analysis indicates that resilient microgrids need to include diverse power sources and/or local energy storage. Then, the presentation moves on to explore suitable power electronic interfaces to integrate diverse power sources, and advanced power distribution architectures to improve resiliency to natural disasters. The effects that these power distribution architectures have on stability and control are also discussed. The presentation concludes with a description of uses of resilient microgrids in key applications, such as wireless communication networks, and an exploration of future research paths.
Alexis Kwasinski earned his M.S. and Ph.D. degrees in electrical engineering from the University of Illinois at Urbana-Champaign (UIUC) in 2005 and 2007, respectively. Previously, he spent almost 10 years working for Telefónica of Argentina and for Lucent Technologies Power Systems. He is currently an Associate Professor in the Department of Electrical and Computer Engineering at The University of Texas at Austin and his research interests include power electronic systems, distributed generation (microgrids), renewable and alternative energy, smart grids, and analysis of the impact of natural disasters on critical power infrastructure. He participated in damage assessments after natural disasters, including hurricane Katrina and the March 2011 earthquake and tsunami in Japan. In 2005, Dr. Kwasinski was awarded the Joseph J. Suozzi INTELEC Fellowship and in 2007 he received the best technical paper award at INTELEC. In 2009 he received an NSF CAREER award and in 2011 he received an IBM Faculty Innovation Award. Dr. Kwasinski is also an Associate Editor for the IEEE Transactions on Energy Conversion and IEEE Transactions on Power Electronics.
Mr. Joel B. Harley, PhD Candidate
Carnegie Mellon University
When: Monday, February 10, 2014 at 3:05 p.m.
Where: Warnock 1230
In engineering and the sciences, there is considerable interest in technology to sense and monitor large-scale, physical environments. These systems have diverse applications in many fields, including civil and aerospace engineering, medicine, oceanography, and seismology. For civil and aerospace applications, these technologies can be used to noninvasively monitor the structural integrity of bridges, pipes, airplanes, and other modern structures. This can reduce maintenance costs and prevent catastrophic failures in our current transportation, power, and resource distribution networks.
Ultrasonic guided waves (waves that are “guided” by the geometry of the environment) have been of particular interest for monitoring critical infrastructures due to their sensitivity to damage and capability to interrogate large areas at once. To detect, locate, and evaluate damage, ultrasonic guided waves are measured and analyzed using various signal processing strategies. However, successfully detecting and locating damage is challenging because the complex propagation environments significantly distort the waves as they travel through the medium.
This talk presents a signal processing framework for overcoming these challenges by combining physical models of ultrasonic waves with novel computational methods and data-driven strategies to learn the complex characteristics of guided waves. We demonstrate how these characteristics can be learned from experimental data and how to leverage this information to improve the detection and localization of damage in critical infrastructures. We also briefly discuss how these strategies can be extended other applications.
Joel B. Harley received the B.S. degree in electrical engineering from Tufts University, Medford, MA, in 2008 and a M.S. degree in electrical and computer engineering from Carnegie Mellon University, Pittsburgh, PA in 2011. He is currently working toward a Ph.D. degree in electrical and computer engineering at Carnegie Mellon University, Pittsburgh, PA. His interests include the integration of complex wave propagation models with novel signal processing, machine learning, and big data methods for applications in cyber-physical systems, structural health monitoring, nondestructive evaluation, and other fields.
Mr. Harley is a recipient of the 2009 National Defense Science and Engineering Graduate (NDSEG) Fellowship, the 2009 National Science Foundation (NSF) Graduate Research Fellowship, the 2009 Department of Homeland Security Graduate Fellowship (declined), and the 2008 Lamme/Westinghouse Electrical and Computer Engineering Graduate Fellowship. He has published more than 30 technical journal and conference papers, including four best student papers. He is a student representative for the IEEE Ultrasonics, Ferroelectrics, and Frequency Control Society, a member of the IEEE Signal Processing Society, and a member of the Acoustical Society of America.
Ms. Katherine Kim, PhD Candidate
University of Illinois at Urbana-Champaign
When: Friday, February 14, 2014 at 3:05 p.m.
Where: Warnock 1230
Photovoltaic (PV) energy systems are gaining popularity in both residential and commercial markets. Traditionally, PV panels are connected in series to a central inverter that maximizes power production and delivers energy to the power grid. When PV cells are connected in series, they often experience mismatch that reduces the total output power. PV mismatch can be caused by various factors, such as non-uniform lighting, partial shading, inconsistent manufacturing, local temperature gradients, and degradation from aging and environmental stress. Dc optimizers are panel-level dc-dc converters that can be used to mitigate this mismatch by independently optimizing each panel’s power. However, dc optimizers must be rated at the full panel power and process all of the power from the PV panel. Differential power processing (DPP) is an alternative solution that achieves high system efficiency by processing a fraction of the total power, while still optimizing power output from each PV panel. DPP converters can also be rated at a lower power level than dc optimizers, which offers potential cost reduction, reliability enhancement, and higher efficiency.
This presentation details the operation of two DPP architectures: PV-to-bus and PV-to-PV. Simulations for both DPP architectures are used to evaluate system performance over 25 years of operation. The level of mismatch among PV panels at 25 years is estimated based on data from long-term field studies. Converter ratings of 15-17% for PV-to-bus and 23-33% for PV-to-PV architectures are identified as appropriate ratings for a 15-submodule PV system. Using Monte Carlo simulation, lifetime performance of the PV-to-bus and PV-to-PV architectures is compared to conventional architectures. DPP converters are shown to deliver 6% more energy compared to the conventional series string architecture at 25 years of operation. This presentation will also speak to future applications of DPP converters in mobile PV applications, such as vehicles and wearable electronics.
Katherine Kim graduated with a B.S. in Electrical and Computer Engineering from Franklin W. Olin College of Engineering in 2007. She received her M.S. in Electrical and Computer Engineering at the University of Illinois at Urbana-Champaign in 2011, and plans to complete her Ph.D. degree in 2014 under Prof. Philip Krein. Katherine’s dissertation research is in power electronics, modeling, control, and protection for photovoltaic systems. She received the National Science Foundation’s East Asia and Pacific Summer Institutes Fellowship in 2010 and Graduate Research Fellowship in 2011. She is currently the Student Membership Chair for the IEEE Power Electronics Society and is active in the student chapter at the University of Illinois.