Dynamic Modeling, Simulation and Control of Energy Generation
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- Hardcover
- Taschenbuch ausgewählt
- eBook
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Sprache:Englisch
103,99 €
UVP
117,69 €
inkl. gesetzl. MwSt.,
Beschreibung
Produktdetails
Einband
Taschenbuch
Erscheinungsdatum
23.08.2016
Abbildungen
XVI, 373 p. 111 illus., 11 illus. in color.
Verlag
Springer LondonSeitenzahl
373
Maße (L/B/H)
23,5/15,5/2,2 cm
Gewicht
593 g
Auflage
Softcover reprint of the original 1st ed. 2013
Sprache
Englisch
ISBN
978-1-4471-6957-4
This book addresses the core issues involved in the dynamic modeling, simulation and control of a selection of energy systems such as gas turbines, wind turbines, fuel cells and batteries. The principles of modeling and control could be applied to other non-convention methods of energy generation such as solar energy and wave energy.
A central feature of
Dynamic Modeling, Simulation and Control of Energy Generation
is that it brings together diverse topics in thermodynamics, fluid mechanics, heat transfer, electro-chemistry, electrical networks and electrical machines and focuses on their applications in the field of energy generation, its control and regulation. This book will help the reader understand the methods of modelling energy systems for controller design application as well as gain a basic understanding of the processes involved in the design of control systems and regulators. It will also be a useful guide to simulation of the dynamics of energy systems andfor implementing monitoring systems based on the estimation of internal system variables from measurements of observable system variables.
Dynamic Modeling, Simulation and Control of Energy Generation
will serve as a useful aid to designers of hybrid power generating systems involving advanced technology systems such as floating or offshore wind turbines and fuel cells. The book introduces case studies of the practical control laws for a variety of energy generation systems based on nonlinear dynamic models without relying on linearization. Also the book introduces the reader to the use nonlinear model based estimation techniques and their application to energy systems.
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