Multi-stage stochastic optimization framework for power generation system planning integrating hybrid uncertainty modelling

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dc.contributor.authorIoannou, Anastasia
dc.contributor.authorFuzuli, Gulistiani
dc.contributor.authorBrennan, Feargal
dc.contributor.authorWidya Yudha, Satya
dc.contributor.authorAngus, Andrew
dc.date.accessioned2019-03-20T11:08:12Z
dc.date.available2019-03-20T11:08:12Z
dc.date.issued2019-03-03
dc.description.abstractIn this paper, a multi-stage stochastic optimization (MSO) method is proposed for determining the medium to long term power generation mix under uncertain energy demand, fuel prices (coal, natural gas and oil) and, capital cost of renewable energy technologies. The uncertainty of future demand and capital cost reduction is modelled by means of a scenario tree configuration, whereas the uncertainty of fuel prices is approached through Monte Carlo simulation. Global environmental concerns have rendered essential not only the satisfaction of the energy demand at the least cost but also the mitigation of the environmental impact of the power generation system. As such, renewable energy penetration, CO2,eq mitigation targets, and fuel diversity are imposed through a set of constraints to align the power generation mix in accordance to the sustainability targets. The model is, then, applied to the Indonesian power generation system context and results are derived for three cases: Least Cost option, Policy Compliance option and Green Energy Policy option. The resulting optimum power generation mixes, discounted total cost, carbon emissions and renewable share are discussed for the planning horizon between 2016 and 2030.en_UK
dc.identifier.citationIoannou a, Fuzuli G, Brennan F, Yudha S and Angus A., Multi-stage stochastic optimization framework for power generation system planning integrating hybrid uncertainty modelling, Energy Economics, Volume 80, Issue May 2019, pp. 760-776.en_UK
dc.identifier.issn0140-9883
dc.identifier.urihttps://doi.org/10.1016/j.eneco.2019.02.013
dc.identifier.urihttp://dspace.lib.cranfield.ac.uk/handle/1826/13999
dc.language.isoenen_UK
dc.publisherElsevieren_UK
dc.rightsAttribution 4.0 International*
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/*
dc.subjectMulti-stage stochastic optimizationen_UK
dc.subjectHybrid uncertainty modellingen_UK
dc.subjectPower generation planningen_UK
dc.subjectscenario treeen_UK
dc.subjectMonte Carlo simulationen_UK
dc.subjectIndonesiaen_UK
dc.titleMulti-stage stochastic optimization framework for power generation system planning integrating hybrid uncertainty modellingen_UK
dc.typeArticleen_UK

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