An energy based security measure for assessing vulnerability to voltage collapse

A security measure is defined to indicate vulnerability to voltage collapse based on an energy function for system models that includes voltage variation and reactive loads. The system dynamic model, the energy function, and the security measure are first illustrated in a simple radial system. Appli...

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Bibliographic Details
Published inIEEE transactions on power systems Vol. 5; no. 2; pp. 419 - 427
Main Authors DeMarco, C.L., Overbye, T.J.
Format Journal Article Conference Proceeding
LanguageEnglish
Published New York, NY IEEE 01.05.1990
Institute of Electrical and Electronics Engineers
Subjects
240100 - Power Systems- (1990-)
296000 - Energy Planning & Policy- Electric Power
Applied sciences
COMPUTER CALCULATIONS
Computer security
CONTROL SYSTEMS
Electric variables measurement
Electrical engineering. Electrical power engineering
Electrical power engineering
Energy measurement
ENERGY MODELS
ENERGY PLANNING, POLICY AND ECONOMY
ENERGY SYSTEMS
Exact sciences and technology
FORECASTING
LOAD MANAGEMENT
Low voltage
MANAGEMENT
Measurement standards
Nonlinear dynamical systems
NONLINEAR PROBLEMS
OUTAGES
Power networks and lines
POWER SYSTEMS
POWER TRANSMISSION AND DISTRIBUTION
Power transmission lines
Reactive power
Student members
Theory. Simulation
Threshold voltage
VAR CONTROL SYSTEMS
Collapse
System evaluation
Critical conditions
Sensitivity
Stability
Reactive load
Measuring system
Voltage
Electric energy
Safety
Lyapunov function
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Summary:A security measure is defined to indicate vulnerability to voltage collapse based on an energy function for system models that includes voltage variation and reactive loads. The system dynamic model, the energy function, and the security measure are first illustrated in a simple radial system. Application of the security measure and its computational aspects are then examined in a standard 30-bus example (New England System). The security measure captures nonlinear effects such as VAR limits on generators that can influence the systems vulnerability to collapse. The behavior of the index with respect to network load increases is nearly linear over a wide range of load variation, facilitating prediction of the onset of collapse.< >
Bibliography:ObjectType-Article-2
SourceType-Scholarly Journals-1
ObjectType-Feature-1
content type line 23
ISSN:0885-8950
1558-0679
DOI:10.1109/59.54548