A framework for the selection of optimum offshore wind farm locations for deployment

Show simple item record

dc.contributor.author Mytilinou, Varvara
dc.contributor.author Lozano-Minguez, Estivaliz
dc.contributor.author Kolios, Athanasios
dc.date.accessioned 2018-08-07T13:46:39Z
dc.date.available 2018-08-07T13:46:39Z
dc.date.issued 2018-07-16
dc.identifier.citation Varvara Mytilinou, Estivaliz Lozano-Minguez and Athanasios Kolios. A framework for the selection of optimum offshore wind farm locations for deployment. Energies, 2018, Volume 11, Issue 7, Article number 1855 en_UK
dc.identifier.issn 1996-1073
dc.identifier.uri https://doi.org/10.3390/en11071855
dc.identifier.uri http://dspace.lib.cranfield.ac.uk/handle/1826/13389
dc.description.abstract This research develops a framework to assist wind energy developers to select the optimum deployment site of a wind farm by considering the Round 3 available zones in the UK. The framework includes optimization techniques, decision-making methods and experts’ input in order to support investment decisions. Further, techno-economic evaluation, life cycle costing (LCC) and physical aspects for each location are considered along with experts’ opinions to provide deeper insight into the decision-making process. A process on the criteria selection is also presented and seven conflicting criteria are being considered for implementation in the technique for the order of preference by similarity to the ideal solution (TOPSIS) method in order to suggest the optimum location that was produced by the nondominated sorting genetic algorithm (NSGAII). For the given inputs, Seagreen Alpha, near the Isle of May, was found to be the most probable solution, followed by Moray Firth Eastern Development Area 1, near Wick, which demonstrates by example the effectiveness of the newly introduced framework that is also transferable and generic. The outcomes are expected to help stakeholders and decision makers to make better informed and cost-effective decisions under uncertainty when investing in offshore wind energy in the UK. en_UK
dc.language.iso en en_UK
dc.publisher MDPI en_UK
dc.rights Attribution 4.0 International *
dc.rights.uri http://creativecommons.org/licenses/by/4.0/ *
dc.subject multi-objective optimization en_UK
dc.subject nondominated sorting genetic algorithm (NSGA) en_UK
dc.subject multi-criteria decision making (MCDM) en_UK
dc.subject technique for the order of preference by similarity to the ideal solution (TOPSIS) en_UK
dc.subject life cycle cost en_UK
dc.title A framework for the selection of optimum offshore wind farm locations for deployment en_UK
dc.type Article en_UK


Files in this item

The following license files are associated with this item:

This item appears in the following Collection(s)

Show simple item record

Attribution 4.0 International Except where otherwise noted, this item's license is described as Attribution 4.0 International

Search CERES


Browse

My Account

Statistics