Multi-criteria decision analysis of offshore wind turbines support structures under stochastic inputs

Selection of the optimum support structural configuration for offshore wind turbines is a decision that should take into account a variety of both technical and non-technical criteria in order to aggregate cumulatively the performance of several concepts such as jackets, tripods, monopiles, spars, s...

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Bibliographic Details
Published in:Ships and offshore structures 2016-01, Vol.11 (1), p.38-49
Main Authors: Kolios, A.J., Rodriguez-Tsouroukdissian, A., Salonitis, K.
Format: Article
Language:English
Subjects:
Decision analysis
decision-making
Numerical analysis
offshore wind turbines
Questionnaires
Shipbuilding
stochastic inputs
Stochastic models
TOPSIS method
Turbines
Online Access:Get full text
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Summary:Selection of the optimum support structural configuration for offshore wind turbines is a decision that should take into account a variety of both technical and non-technical criteria in order to aggregate cumulatively the performance of several concepts such as jackets, tripods, monopiles, spars, semi-subs, tri-floaters and others with varying suitability and relevance to offshore wind applications. In the preliminary phases of a project, consideration of qualitative attributes based on experts' opinions is a common practice due to the limited availability of quantitative data for attribute scores and relevant weights, which are mainly based on past experience. This practice can introduce a bias in the considered scores reducing the confidence of the qualifying solution. This paper documents the extension of the widely used TOPSIS method (Technique for Order of Preference by Similarity to Ideal Solution) to explicitly consider stochastic inputs (statistical distributions) following a systematic gathering of data through surveys and questionnaires. The methodology proposed has been efficiently implemented in a numerical tool and the case study that is presented on the decision analysis of an offshore wind turbine supports structure under given deployment conditions, illustrates its applicability and allows for a sensitivity analysis of the effect of the resolution of simulation, selection of statistical distributions and weighting of experts' opinions based on their perceived level of expertise.
ISSN:1744-5302
1754-212X
DOI:10.1080/17445302.2014.961295