Invited Speakers

Stochastic Analysis of Real and Virtual Energy Storage in the Smart Grid
Jean-Yves Le Boudec
, EPFL

(Joint work with Nicolas Gast and Dan-Cristian Tomozei)

Energy storage and demand response are used in the smart grid to compensate for fluctuations and forecasting errors in demand and production. Demand response can also be used as a form of storage, where load rather than supply is stored. In the first part of this talk, we propose a system wide model for real time demand response. The model shows that evaporation, namely the fraction of delayed demand that eventually disappears, plays a central role. Further, large backlogs of delayed demand may accumulate. In a second part, we study a model of real storage, using pump hydro. We revisit an existing study by Bejan et al.; we study the impact of energy conversion efficiency and of the quality of wind predictions. We study storage control policies and find strategies that outperform the proposed fixed level policies.

Branch Flow Model: Relaxations, Convexification, Computation
Steven Low, Caltech

We propose a branch flow model for the analysis and optimization of mesh as well as radial networks. The model leads to a new approach to solving optimal power flow (OPF) problems that consists of two relaxation steps. The first step eliminates the voltage and current angles and the second step approximates the resulting problem by a conic program that can be solved efficiently. For radial networks, we prove that both relaxation steps are always exact, provided there are no upper bounds on loads. For mesh networks, the conic relaxation is always exact and we characterize when the angle relaxation may fail. We propose a simple method to convexify a mesh network using phase shifters so that both relaxation steps are always exact and OPF for the convexified network can always be solved efficiently for a globally optimal solution. We prove that convexification requires phase shifters only outside a spanning tree of the network graph and their placement depends only on network topology, not on power flows, generation, loads, or operating constraints. Since power networks are sparse, the number of required phase shifters may be relatively small. We present a simple scalable distributed solution that can be easily parallelized or implemented on a large power network. Finally, we relate this model to the popular bus injection model and semidefinite relaxation.

(Joint work with Masoud Farivar, Lingwen Gan, Subhonmesh Bose, Mani Chandy, Caltech)

Steven H. Low is a Professor of the Computing & Mathematical Sciences and Electrical Engineering Departments at Caltech, and an adjunct professor of both the Swinburne University, Australia and the Shanghai Jiao Tong University, China. Before that, he was with AT&T Bell Laboratories, Murray Hill, NJ, and the University of Melbourne, Australia. He was a co-recipient of IEEE best paper awards, the R&D 100 Award, and an Okawa Foundation Research Grant. He was on the editorial boards of IEEE/ACM Transactions on Networking, IEEE Transactions on Automatic Control, ACM Computing Surveys, Computer Networks Journal, NOW Foundations and Trends in Networking. He is a Senior Editor of the IEEE JSAC. He is an IEEE Fellow, and received his B.S. from Cornell and PhD from Berkeley, both in EE.


Challenges in Multi-Modal Transport Planning
Jochen Mundinger, routeRANK Ltd

Jochen Mundinger is founder and Chairman of routeRANK Ltd. He graduated in mathematics with computer science from Gonville and Caius College, Cambridge, in 2001. In 2002 he obtained his M.Phil. and in 2005 his Ph.D. at the Statistical Laboratory, Cambridge. He has been awarded numerous scholarships and prizes. Prior to starting routeRANK, Jochen was a senior researcher at the Swiss Federal Institute of Technology in Lausanne (EPFL).
Real-Time Distributed Control of Electrical Vehicle Charging
Catherine Rosenberg, University of Waterloo

The significant load and unpredictable mobility of electric vehicles (EVs) makes them a challenge for grid distribution systems. Unlike most current approaches to control EV charging, which construct optimal charging schedules by predicting EV state of charge and future behaviour, we leverage the anticipated widespread deployment of measurement and control points to propose an alternative vision. In our approach, drawing from a comparative analysis of Internet and distribution grid congestion, control actions taken by a charger every few milliseconds in response to congestion signals allow it to rapidly reduce its charging rate to avoid grid congestion. We sketch three control schemes that embody this vision and compare their relative merits and demerits.

Catherine Rosenberg is a professor in Electrical and Computer Engineering at the University of Waterloo. Since June 2010, she holds the Canada Research Chair in the Future Internet. She started her career at Alcatel in France and then worked at AT&T Bell Labs in the U.S. From 1988-1996, she was a faculty member at the Department of Electrical and Computer Engineering, Ecole Polytechnique, in Montreal, Canada. In 1996, she joined Nortel Networks in the United Kingdom where she created and headed the R&D Department in Broadband Satellite Networking. In August 1999, Dr. Rosenberg became a professor in the School of Electrical and Computer Engineering at Purdue University where she co-founded the Center for Wireless Systems and Applications (CWSA) in May 2002. She joined the University of Waterloo on September 1, 2004, as the Chair of the Department of Electrical and Computer Engineering for a three-year term. Rosenberg is on the Scientific Advisory Board of France-Telecom and is a fellow of the IEEE. She co-founded ISS4E, a research lab on smart grids with S. Keshav in 2010.
Evaluation of the Impacts of Geographically-Correlated Failures on Power Grids
Gil Zussman, Columbia University

In this talk, we consider power line outages in the transmission system of the power grid, and specifically those caused by a natural disaster or a large scale physical attack. We present an analytical model of such geographically correlated failures, investigate the model's properties, and show that it differs from other models used to analyze cascades in the power grid. We then show how to identify the most vulnerable locations in the grid and perform extensive numerical experiments with real grid data to investigate the various effects of geographically correlated outages and the resulting cascades.

Joint work with Andrey Bernstein (Technion), Daniel Bienstock (Columbia University), David Hay (Hebrew University), and Meric Uzunoglu (Columbia University).

Gil Zussman received the Ph.D. degree in Electrical Engineering from the Technion in 2004. Between 2004 and 2007 he was a Postdoctoral Associate at MIT. He is an Assistant Professor of Electrical Engineering at Columbia University. He has been an associate editor of IEEE Transactions on Wireless Communications and Ad Hoc Networks, and the TPC co-chair of IFIP Performance 2011. He is a co-recipient of 4 best paper awards including the ACM SIGMETRICS 2006 Best Paper Award and the 2011 IEEE Communications Society Award for Advances in Communication. He was a member of a team that won the 1st place in the 2009 Vodafone Foundation Wireless Innovation competition and is a recipient of the Fulbright Fellowship, the Marie Curie Outgoing International Fellowship, the DTRA Young Investigator Award, and the NSF CAREER Award.