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Renewables in Future Power Systems Implications of Technological Learning and Uncertainty /

The book examines the future deployment of renewable power from a normative point of view. It identifies properties characterizing the cost-optimal transition towards a renewable power system and analyzes the key drivers behind this transition. Among those drivers, particular attention is paid to te...

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Detalles Bibliográficos
Clasificación:Libro Electrónico
Autor principal: Wagner, Fabian (Autor)
Autor Corporativo: SpringerLink (Online service)
Formato: Electrónico eBook
Idioma:Inglés
Publicado: Cham : Springer International Publishing : Imprint: Springer, 2014.
Edición:1st ed. 2014.
Colección:Green Energy and Technology,
Temas:
Acceso en línea:Texto Completo

MARC

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245 1 0 |a Renewables in Future Power Systems  |h [electronic resource] :  |b Implications of Technological Learning and Uncertainty /  |c by Fabian Wagner. 
250 |a 1st ed. 2014. 
264 1 |a Cham :  |b Springer International Publishing :  |b Imprint: Springer,  |c 2014. 
300 |a XVI, 291 p. 70 illus., 14 illus. in color.  |b online resource. 
336 |a text  |b txt  |2 rdacontent 
337 |a computer  |b c  |2 rdamedia 
338 |a online resource  |b cr  |2 rdacarrier 
347 |a text file  |b PDF  |2 rda 
490 1 |a Green Energy and Technology,  |x 1865-3537 
505 0 |a Introduction -- Renewables in power generation: Status quo -- Methods for energy system modeling -- Technological change and the experience curve -- Optimal investment strategy for competing learning technologies: An analytical approach -- Optimal future deployment of renewable power technologies: A system model approach -- Implications of uncertainty for renewable power deployment -- Summary and outlook. 
520 |a The book examines the future deployment of renewable power from a normative point of view. It identifies properties characterizing the cost-optimal transition towards a renewable power system and analyzes the key drivers behind this transition. Among those drivers, particular attention is paid to technological cost reductions and the implications of uncertainty. From a methodological perspective, the main contributions of this book relate to the field of endogenous learning and uncertainty in optimizing energy system models. The primary objective here is closing the gap between the strand of literature covering renewable potential analyses on the one side and energy system modeling with endogenous technological change on the other side. The models applied in this book demonstrate that fundamental changes must occur to transform today's power sector into a more sustainable one over the course of this century. Apart from its methodological contributions, this work is also intended to provide practically relevant insights regarding the long-term competitiveness of renewable power generation.  . 
650 0 |a Renewable energy sources. 
650 0 |a Dynamics. 
650 0 |a Nonlinear theories. 
650 0 |a Economic development. 
650 0 |a Energy policy. 
650 0 |a Energy and state. 
650 1 4 |a Renewable Energy. 
650 2 4 |a Applied Dynamical Systems. 
650 2 4 |a Economic Development, Innovation and Growth. 
650 2 4 |a Energy Policy, Economics and Management. 
710 2 |a SpringerLink (Online service) 
773 0 |t Springer Nature eBook 
776 0 8 |i Printed edition:  |z 9783319057811 
776 0 8 |i Printed edition:  |z 9783319057798 
776 0 8 |i Printed edition:  |z 9783319359892 
830 0 |a Green Energy and Technology,  |x 1865-3537 
856 4 0 |u https://doi.uam.elogim.com/10.1007/978-3-319-05780-4  |z Texto Completo 
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950 |a Energy (SpringerNature-40367) 
950 |a Energy (R0) (SpringerNature-43717)