Sangam: A Confluence of Knowledge Streams

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

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dc.creator Mytilinou, Varvara
dc.creator Lozano-Minguez, Estivaliz
dc.creator Kolios, Athanasios
dc.date 2018-08-07T13:46:39Z
dc.date 2018-08-07T13:46:39Z
dc.date 2018-07-16
dc.date.accessioned 2022-05-25T16:37:35Z
dc.date.available 2022-05-25T16:37:35Z
dc.identifier 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
dc.identifier 1996-1073
dc.identifier https://doi.org/10.3390/en11071855
dc.identifier http://dspace.lib.cranfield.ac.uk/handle/1826/13389
dc.identifier.uri http://localhost:8080/xmlui/handle/CUHPOERS/182247
dc.description 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.
dc.language en
dc.publisher MDPI
dc.rights Attribution 4.0 International
dc.rights http://creativecommons.org/licenses/by/4.0/
dc.subject multi-objective optimization
dc.subject nondominated sorting genetic algorithm (NSGA)
dc.subject multi-criteria decision making (MCDM)
dc.subject technique for the order of preference by similarity to the ideal solution (TOPSIS)
dc.subject life cycle cost
dc.title A framework for the selection of optimum offshore wind farm locations for deployment
dc.type Article


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