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

Mytilinou, Varvara and Lozano-Minguez, Estivaliz and Kolios, Athanasios (2018) A framework for the selection of optimum offshore wind farm locations for deployment. Energies, 11 (7). 1855. ISSN 1996-1073

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    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.

    ORCID iDs

    Mytilinou, Varvara, Lozano-Minguez, Estivaliz and Kolios, Athanasios ORCID logoORCID: https://orcid.org/0000-0001-6711-641X;
    • Item type:Article
      ID code:65686
      Dates:
      Date
      Event
      16 July 2018
      Published
      9 July 2018
      Accepted
      Keywords:life cycle cost, multi-criteria decision making (MCDM), multi-objective optimization, nondominated sorting genetic algorithm (NSGA), technique for the order of preference by similarity to the ideal solution (TOPSIS), Hydraulic engineering. Ocean engineering, Renewable Energy, Sustainability and the Environment, Electrical and Electronic Engineering
      Subjects:Technology > Hydraulic engineering. Ocean engineering
      Department:Faculty of Engineering > Naval Architecture, Ocean & Marine Engineering
      Depositing user: Pure Administrator
      Date deposited:04 Oct 2018 11:50
      Last modified:29 Oct 2021 00:47
      Related URLs:
      URI:https://strathprints.strath.ac.uk/id/eprint/65686
    CORE (COnnecting REpositories)