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IMA Tutorial
Control and Pricing in Communication and Power Networks
March 7, 2004


Probability and Statistics in Complex Systems: Genomics, Networks, and Financial Engineering, September 1, 2003 - June 30, 2004

Organizers:

Christopher L. DeMarco
Department of Electrical and Computer Engineering
University of Wisconsin-Madison
demarco@engr.wisc.edu
http://www.engr.wisc.edu/ece/faculty/demarco_christopher.html

Thomas G. Kurtz
Center for Mathematical Sciences
University of Wisconsin-Madison
kurtz@math.wisc.edu

http://www.math.wisc.edu/~kurtz/

Ruth J. Williams
Department of Mathematics
University of California, San Diego
williams@math.ucsd.edu
http://math.ucsd.edu/~williams/

The tutorial will introduce some of the main issues in the design and operation of communication and power networks and will provide background helpful in understanding the material to be presented during the Workshop. While the connectivity of power and communications networks may be similar, the physics of these networks is very different. The tutorial and the following workshop should provide a better understanding of both the similarities and the differences in these systems.

TUTORIAL SCHEDULE
SUNDAY, MARCH 7,
All talks are in Lecture Hall EE/CS 3-180 unless otherwise noted.
8:30 Coffee and Registration

Reception Room EE/CS 3-176

9:00 AM Douglas N. Arnold, Scot Adams, and Organizers Welcome and Introduction
9:15-10:15 AM Christopher L. DeMarco

Models for the Electric Power Grid

Slides:   pdf

10:45-12:00 Noon R. Srikant

The Architecture of the Internet

Slides:   html   pdf    ps    ppt

1:30-2:45 PM Christopher L. DeMarco

Cascading Failures in Power Networks

Slides:   pdf

3:15-4:30 PM R. Srikant

Pricing and Control of the Internet

Slides:   html   pdf    ps    ppt

4:30 PM
Questions and Further Discussion

Abstracts

Network Control, Pricing, and the Role of Cascading Failure Phenomena in Electric Power Grids
Christopher L. DeMarco, University of Wisconsin - Madison

While sharing a number of broad qualitative features with problems in control and resource allocation for other large scale networks such as the internet, electric power grids present a range of unique challenges. Three major technological characteristics distinguish control and pricing problems in electric power: (i) the commodity being delivered is inefficient to store, so production tracks consumption across the entire interconnected grid, nearly instantaneously; (ii) the majority of branches in the delivery network are passive elements, with branch flows dictated by nonlinear relations to nodal boundary conditions, rather than by direct control; (iii) many constraints on operation represent physical limits whose violation can yield costly equipment damage and threats to human safety. Adding to the complexity of analysis is the U.S. electric power system's uneven regulatory policy transition, in which certain physical elements contributing to grid control operate in competitive markets (generators), while the others (e.g., switched capacitor banks, adjustable tap transformers) operate under the authority of regulated regional transmission monopolies.

This tutorial will give an overview of the mathematical models used to predict both dynamic and steady state performance of physical quantities in the electric power grid. Starting from the nonlinear constraints on network power flow, and the nature of financial offers and bids for electric power production and consumption, the relation of so-called "locational marginal prices" to an underlying optimization formulation will be reviewed. Issues in developing effective offer and bid strategies from these locational prices, and related issues for setting regulatory structures to govern these, will be highlighted. The tutorial will conclude with an overview of techniques for predicting cascading failure phenomena. Research to improve these techniques could play a key role in balancing operational strategies that favor efficiency under "normal" conditions, versus strategies that favor mitigation of risk of extremely high cost, low probability failure events such as the eastern U.S. blackout of August 2003.

Pricing and Control for the Internet
R. Srikant
, University of Illinois, Urbana-Champaign

In the first part of the tutorial, we will present a general introduction to the architecture of the Internet. Various protocols for scheduling, admission control, routing and congestion control will be introduced. We will then focus our attention on TCP, the widely-used protocol for file transfer in the Internet today. Jacobson's TCP congestion control algorithm has been remarkably successful in regulating file transfers and facilitating the phenomenal growth of the Internet over the last decade. This congestion control mechanism was designed for networks where the required data rate per user is small (less than one Mbps) and the round-trip times are small (of the order of a few milliseconds). However, access speeds, application requirements and file transfer distances continue to increase. Using simple tools from queueing theory and delay-differential equations, we will illustrate the need to redesign the congestion management mechanisms in the Internet to efficiently deliver high data rates over long distances.

In the second part of the tutorial, we will concentrate on pricing and control mechanisms that have recently led to the design of scalable TCP protocols. Starting with Kelly's model of resource allocation in a heterogeneous Internet, it will be shown that congestion management can be viewed as a distributed algorithm for fair resource allocation in the Internet. We will illustrate the use of tools from convex optimization, stochastic processes and control theory in designing congestion control mechanisms at the end users and congestion indication mechanisms at the routers that deliver an efficient loss-free, delay-free service over the Internet.

LIST OF CONFIRMED PARTICIPANTS

NAMEDEPARTMENTAFFILIATION
Scot AdamsInstitute for Mathematics and its Applications University of Minnesota, Twin Cities
Inkyung AhnDepartment of Mathematics Korea University
Greg AndersonSchool of Mathematics University of Minnesota, Twin Cities
Douglas ArnoldInstitute for Mathematics and its Applications University of Minnesota, Twin Cities
Donald AronsonInstitute for Mathematics and its Applications University of Minnesota, Twin Cities
Gerard AwanouInstitute for Mathematics and its Applications University of Minnesota, Twin Cities
Karen BallInstitute for Mathematics and its Applications University of Minnesota, Twin Cities
Antar BandyopadhyayInstitute for Mathematics and its Applications University of Minnesota, Twin Cities
Maury BramsonSchool of Mathematics University of Minnesota, Twin Cities
James Carson RisQuant Energy
Michael ChenCoordinated Science Laboratory University of Illinois at Urbana-Champaign
Wanyang DaiDepartment of Mathematics Nanjing University
Christopher DeMarcoDepartment of Electrical and Computer Engineering University of Wisconsin, Madison
Shi-Jie DengDepartment of Industrial and Systems Engineering Georgia Institute of Technology
Shmuel FriedlandDepartment of Mathematics, Statistics, and Computer Science University of Illinois, Chicago
Tim GaroniInstitute for Mathematics and its Applications University of Minnesota, Twin Cities
Art GuetterDepartment of Mathematics Hamlin University
Bruce HajekDepartment of Electrical and Computer Engineering University of Illinois at Urbana-Champaign
Chuan-Hsiang HanInstitute for Mathematics and its Applications University of Minnesota, Twin Cities
Naresh JainSchool of Mathematics University of Minnesota, Twin Cities
Ramesh JohariLaboratory for Information and Decision Systems Massachusetts Institute of Technology
Lili JuInstitute for Mathematics and its Applications University of Minnesota, Twin Cities
Herve KerivinInstitute for Mathematics and its Applications University of Minnesota, Twin Cities
Peter Key Microsoft Research
Mohammad KhanDepartment of Mathematics Kent State University
Hye-Ryoung Kim Seoul National University
Thomas KurtzDepartment of Mathematics University of Wisconsin, Madison
Peter Kuznia Hamline University
Nam LeeDepartment of Mathematics University of California, San Diego
Ioannis LestasDepartment of Engineering University of Cambridge
David McDonaldDepartment of Mathematics University of Ottawa
Richard McGeheeSchool of Mathematics University of Minnesota, Twin Cities
Sean MeynDepartment of Electrical and Computer Engineering University of Illinois at Urbana-Champaign
Haewon NamInstitute of Mathematics and Statistics University of Minnesota, Twin Cities
Amir NiknejadDepartment of Mathematics University of Illinois, Chicago
Asuman OzdaglarDepartment of Electrical Engineering and Computer Science Massachusetts Institute of Technology
Lea PopovicInstitute for Mathematics and its Applications University of Minnesota, Twin Cities
Kavita RamananDepartment of Mathematical Sciences Alcatel-Lucent Technologies Bell Laboratories
Martin ReimanBell Laboratories Alcatel-Lucent Technologies Bell Laboratories
Grzegorz RempalaDepartment of Mathematics University of Louisville
Sara Robinson SIAM
Fadil SantosaInstitute for Mathematics and its Applications University of Minnesota, Twin Cities
Arnd ScheelSchool of Mathematics University of Minnesota, Twin Cities
R. SrikantDepartment of Electrical and Computer Engineering University of Illinois at Urbana-Champaign
Cortin Stelter Hamline University
Tamon StephenInstitute of Mathematics and its Application University of Minnesota, Twin Cities
Hui WangDivision of Applied Mathematics Brown University
Jing WangInstitute for Mathematics and its Applications University of Minnesota, Twin Cities
Ruth WilliamsDepartment of Mathematics University of California, San Diego
Yuhong YangDepartment of Statistics Iowa State University
William YurcikDepartment of NCSA University of Illinois at Urbana-Champaign
Ofer ZeitouniSchool of Mathematics University of Minnesota, Twin Cities
Jun ZhaoInstitute of Mathematics and its Application University of Minnesota, Twin Cities
Ilze ZiedinsDepartment of Statistics University of Auckland
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