Strategic power plant investment planning under fuel and carbon price uncertainty

dc.contributor.author	Geiger, Ansgar	*
dc.date.accessioned	2021-02-12T04:39:26Z
dc.date.available	2021-02-12T04:39:26Z
dc.date.issued	2011	*
dc.date.submitted	2019-07-30 20:02:02	*
dc.identifier	35634	*
dc.identifier.uri	https://directory.doabooks.org/handle/20.500.12854/60100
dc.description.abstract	The profitability of power plant investments depends strongly on uncertain fuel and carbon prices. In this doctoral thesis, we combine fundamental electricity market models with stochastic dynamic programming to evaluate power plant investments under uncertainty. The application of interpolation-based stochastic dynamic programming and approximate dynamic programming allows us to consider a greater variety of stochastic fuel and carbon price scenarios compared to other approaches.	*
dc.language	English	*
dc.subject	HF5001-6182	*
dc.subject.other	Real Options	*
dc.subject.other	Dynamic Programming	*
dc.subject.other	Fundamental Electricity Market Models	*
dc.subject.other	Power Plant Investment Planning	*
dc.subject.other	Approximate Dynamic Programming	*
dc.title	Strategic power plant investment planning under fuel and carbon price uncertainty	*
dc.type	book
oapen.identifier.doi	10.5445/KSP/1000021824	*
oapen.relation.isPublishedBy	68fffc18-8f7b-44fa-ac7e-0b7d7d979bd2	*
virtual.oapen_relation_isPublishedBy.publisher_name	KIT Scientific Publishing
virtual.oapen_relation_isPublishedBy.publisher_website	http://www.ksp.kit.edu/
oapen.relation.isbn	9783866446335	*
oapen.pages	XVIII, 306 p.	*

Files in this item

Files	Size	Format	View
There are no files associated with this item.

Except where otherwise noted, this item's license is described as https://creativecommons.org/licenses/by-nc-nd/4.0/