Stochastic prediction of offshore wind farm LCOE through an integrated cost model

Simple item page
dc.contributor.authorIoannou, Anastasia
dc.contributor.authorAngus, Andrew
dc.contributor.authorBrennan, Feargal P.
dc.date.accessioned2017-03-27T13:41:52Z
dc.date.available2017-03-27T13:41:52Z
dc.date.issued2017-03-09
dc.description.abstractCommon deterministic cost of energy models applied in offshore wind energy installations usually disregard the effect of uncertainty of key input variables – associated with OPEX, CAPEX, energy generation and other financial variables – on the calculation of levelized cost of electricity (LCOE). The present study aims at expanding a deterministic cost of energy model to systematically account for stochastic inputs. To this end, Monte Carlo simulations are performed to derive the joint probability distributions of LCOE, allowing for the estimation of probabilities of exceeding set thresholds of LCOE, determining certain confidence intervals. The results of this study stress the importance of appropriate statistical modelling of stochastic variables in order to reduce modelling uncertainties and contribute to a better informed decision making in renewable energy investments.en_UK
dc.identifier.citationIoannou A, Angus A, Brennan F, Stochastic prediction of offshore wind farm LCOE through an integrated cost model, Energy Procedia, Volume 107, February 2017, Pages 383-389.en_UK
dc.identifier.issn1876-6102
dc.identifier.urihttp://dx.doi.org/10.1016/j.egypro.2016.12.180
dc.identifier.urihttp://dspace.lib.cranfield.ac.uk/handle/1826/11664
dc.language.isoenen_UK
dc.publisherElsevieren_UK
dc.rightsAttribution 4.0 International (CC BY 4.0) You are free to: Share — copy and redistribute the material in any medium or format, Adapt — remix, transform, and build upon the material for any purpose, even commercially. The licensor cannot revoke these freedoms as long as you follow the license terms. Under the following terms: Attribution — You must give appropriate credit, provide a link to the license, and indicate if changes were made. You may do so in any reasonable manner, but not in any way that suggests the licensor endorses you or your use. Information: No additional restrictions — You may not apply legal terms or technological measures that legally restrict others from doing anything the license permits.
dc.subjectOffshore wind farmen_UK
dc.subjectprobabilistic cost modelen_UK
dc.subjectMonte Carlo simulationen_UK
dc.subjectlevelised cost of electricityen_UK
dc.subjectstochastic inputsen_UK
dc.titleStochastic prediction of offshore wind farm LCOE through an integrated cost modelen_UK
dc.typeArticleen_UK

Files

Original bundle
Now showing 1 - 1 of 1
Thumbnail Image
Name:
Stochastic_prediction_of_offshore_wind_farm-2017.pdf
Size:
257.5 KB
Format:
Adobe Portable Document Format
Download
License bundle
Now showing 1 - 1 of 1
No Thumbnail Available
Name:
license.txt
Size:
1.79 KB
Format:
Item-specific license agreed upon to submission
Description:
Download

Collections

Staff publications (SWEE)