Network and Load Modeling for Power System Dynamic Analysis
Lesieutre, Bernard Charles
This item is only available for download by members of the University of Illinois community. Students, faculty, and staff at the U of I may log in with your NetID and password to view the item. If you are trying to access an Illinois-restricted dissertation or thesis, you can request a copy through your library's Inter-Library Loan office or purchase a copy directly from ProQuest.
Permalink
https://hdl.handle.net/2142/71992
Description
Title
Network and Load Modeling for Power System Dynamic Analysis
Author(s)
Lesieutre, Bernard Charles
Issue Date
1993
Doctoral Committee Chair(s)
Sauer, Peter W.
Department of Study
Electrical Engineering
Discipline
Electrical Engineering
Degree Granting Institution
University of Illinois at Urbana-Champaign
Degree Name
Ph.D.
Degree Level
Dissertation
Keyword(s)
Engineering, Electronics and Electrical
Abstract
This thesis involves the development of network and load models for power system analysis. Traditional power system models consist of detailed generator models and simple network and load models. In the past this has been acceptable as these models captured observed phenomena. These models do not sufficiently describe the system under heavily loaded conditions; in fact, the mathematical equations may not exhibit a solution. This is unacceptable. The problem is that the form of traditional load models is chosen for convenience and is not based on actual load dynamics. In this thesis, network and load models are presented that capture important frequency and voltage dependencies. Conditions on a common class of static load models are given to ensure that the power system algebraic equations will exhibit a solution. An induction motor model is used to justify dynamic load models that appear in the literature and to develop new models. These models are important because they are based on physical motor characteristics. Steady-state, transient, and structural stability studies are performed to examine the effects of different static and induction motor loads.
Use this login method if you
don't
have an
@illinois.edu
email address.
(Oops, I do have one)
IDEALS migrated to a new platform on June 23, 2022. If you created
your account prior to this date, you will have to reset your password
using the forgot-password link below.