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Title:Dynamic-Data Driven Real-Time Identification for Electric Power Systems
Author(s):Liu, Shanshan
Director of Research:Sauer, Peter W.
Doctoral Committee Chair(s):Sauer, Peter W.
Doctoral Committee Member(s):Namachchivaya, N. Sri; Overbye, Thomas J.; Pai, M.A.
Department / Program:Electrical and Computer Engineering
Discipline:Electrical and Computer Engineering
Degree Granting Institution:University of Illinois at Urbana-Champaign
Subject(s):Load modeling
Nonlinear filtering
State estimation
Order reduction
Balanced truncation
Abstract:Power system engineers face a double challenge: to operate electric power systems within narrow stability and security margins, and to maintain high reliability. There is an acute need to better understand the dynamic nature of power systems in order to be prepared for critical situations as they arise. Innovative measurement tools, such as phasor measurement units, can capture not only the slow variation of the voltages and currents but also the underlying oscillations in a power system. Such dynamic data accessibility provides us a strong motivation and a useful tool to explore dynamic-data driven applications in power systems. To fulfill this goal, this dissertation focuses on the following three areas: Developing accurate dynamic load models and updating variable parameters based on the measurement data, applying advanced nonlinear filtering concepts and technologies to real-time identification of power system models, and addressing computational issues by implementing the balanced truncation method. By obtaining more realistic system models, together with timely updated parameters and stochastic influence consideration, we can have an accurate portrait of the ongoing phenomena in an electrical power system. Hence we can further improve state estimation, stability analysis and real-time operation.
Issue Date:2009-06-01
Rights Information:Copyright 2009 Shanshan Liu
Date Available in IDEALS:2009-06-01
Date Deposited:May 2009

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