A Framework for the Selection of Optimum Offshore Wind Farm Locations for Deployment
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 inve...
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| Format: | Article |
| Language: | English |
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MDPI AG
2018-07-01
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| Series: | Energies |
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| Online Access: | http://www.mdpi.com/1996-1073/11/7/1855 |
| _version_ | 1817994329410502656 |
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| author | Varvara Mytilinou Estivaliz Lozano-Minguez Athanasios Kolios |
| author_facet | Varvara Mytilinou Estivaliz Lozano-Minguez Athanasios Kolios |
| author_sort | Varvara Mytilinou |
| collection | DOAJ |
| 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. |
| first_indexed | 2024-04-14T01:51:26Z |
| format | Article |
| id | doaj.art-3912365ff6f0449a9a6abeb713a190ce |
| institution | Directory Open Access Journal |
| issn | 1996-1073 |
| language | English |
| last_indexed | 2024-04-14T01:51:26Z |
| publishDate | 2018-07-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Energies |
| spelling | doaj.art-3912365ff6f0449a9a6abeb713a190ce2022-12-22T02:19:20ZengMDPI AGEnergies1996-10732018-07-01117185510.3390/en11071855en11071855A Framework for the Selection of Optimum Offshore Wind Farm Locations for DeploymentVarvara Mytilinou0Estivaliz Lozano-Minguez1Athanasios Kolios2Renewable Energy Marine Structures Centre for Doctoral Training, Cranfield University, Cranfield, Bedfordshire MK43 0AL, UKDepartment of Mechanical Engineering and Materials—CIIM, Universitat Politècnica de València, Camino de Vera s/n, 46022 Valencia, SpainDepartment of Naval Architecture, Ocean & Marine Engineering, University of Strathclyde, HD2.35, Henry Dyer Building, 100 Montrose Street, Glasgow G4 0LZ, UKThis 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.http://www.mdpi.com/1996-1073/11/7/1855multi-objective optimizationnondominated sorting genetic algorithm (NSGA)multi-criteria decision making (MCDM)technique for the order of preference by similarity to the ideal solution (TOPSIS)life cycle cost |
| spellingShingle | Varvara Mytilinou Estivaliz Lozano-Minguez Athanasios Kolios A Framework for the Selection of Optimum Offshore Wind Farm Locations for Deployment Energies multi-objective optimization nondominated sorting genetic algorithm (NSGA) multi-criteria decision making (MCDM) technique for the order of preference by similarity to the ideal solution (TOPSIS) life cycle cost |
| title | A Framework for the Selection of Optimum Offshore Wind Farm Locations for Deployment |
| title_full | A Framework for the Selection of Optimum Offshore Wind Farm Locations for Deployment |
| title_fullStr | A Framework for the Selection of Optimum Offshore Wind Farm Locations for Deployment |
| title_full_unstemmed | A Framework for the Selection of Optimum Offshore Wind Farm Locations for Deployment |
| title_short | A Framework for the Selection of Optimum Offshore Wind Farm Locations for Deployment |
| title_sort | framework for the selection of optimum offshore wind farm locations for deployment |
| topic | multi-objective optimization nondominated sorting genetic algorithm (NSGA) multi-criteria decision making (MCDM) technique for the order of preference by similarity to the ideal solution (TOPSIS) life cycle cost |
| url | http://www.mdpi.com/1996-1073/11/7/1855 |
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