Power System Coherency and Model Reduction
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Beschreibung
"Power System Coherency and Model Reduction" provides a comprehensive treatment for understanding interarea modes in large power systems and obtaining reduced-order models using the coherency concept and selective modal analysis method.
Both linear and nonlinear analysis methods are covered. The ideas in this book are important for designing damping control of interarea modes. Small system examples to illustrate the concepts and large power system examples to illustrate practical applications of the method are included. This is an important reference book for researchers interested in interarea oscillations and model reduction, and power engineers in developing reduced models for power system studies and control design.
"Power System Coherency and Model Reduction" provides a comprehensive treatment for understanding interarea modes in large power systems and obtaining reduced-order models using the coherency concept and selective modal analysis method. Both linear and nonlinear analysis methods are covered. This is a reference book for researchers interested in interarea oscillations and model reduction, and power engineers in developing reduced models for power system studies and control design.
Provides methods to identify coherent machines and develop reduced order models Discusses a model reduction program suitable for large power systems Provides engineering insights in using coherency and model reduction methods
Autor*in
Joe H. Chow
Themen in »Power System Coherency and Model Reduction«
Coherency in power systems External system reduction Interarea modes Interarea oscillations Krylov subspace method Large power systems Machine aggregation Perturbation techniques Selective modal analysis
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From the reviews:
“I enjoyed reading this monograph and would highly recommend it. It is an excellent reference providing an overview of power system coherency, model reduction, and related problems by integrating analytical bases, engineering practices, emerging techniques, and insights, which would benefit both engineers and researchers in the fields of power system dynamics. ” (Kai Sun, IEEE power & energy magazine, January-February, 2014)()