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dc.contributor.authorGeiger, Ansgar*
dc.date.accessioned2021-02-12T04:39:26Z
dc.date.available2021-02-12T04:39:26Z
dc.date.issued2011*
dc.date.submitted2019-07-30 20:02:02*
dc.identifier35634*
dc.identifier.urihttps://directory.doabooks.org/handle/20.500.12854/60100
dc.description.abstractThe 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.languageEnglish*
dc.subjectHF5001-6182*
dc.subject.otherReal Options*
dc.subject.otherDynamic Programming*
dc.subject.otherFundamental Electricity Market Models*
dc.subject.otherPower Plant Investment Planning*
dc.subject.otherApproximate Dynamic Programming*
dc.titleStrategic power plant investment planning under fuel and carbon price uncertainty*
dc.typebook
oapen.identifier.doi10.5445/KSP/1000021824*
oapen.relation.isPublishedBy68fffc18-8f7b-44fa-ac7e-0b7d7d979bd2*
virtual.oapen_relation_isPublishedBy.publisher_nameKIT Scientific Publishing
virtual.oapen_relation_isPublishedBy.publisher_websitehttp://www.ksp.kit.edu/
oapen.relation.isbn9783866446335*
oapen.pagesXVIII, 306 p.*


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