Application and extension of the TOPSIS method for the assessment of floating offshore wind turbine support structures

Martin, Heather R.; Spano, G.; Küster, J. F.; Collu, Maurizio; Kolios, Athanasios

doi:10.1080/17445302.2012.718957

Cited by 33 publications

(14 citation statements)

References 8 publications

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“…These were selected so as to extend previous work and for comparison purposes [18,21,75,77,78]. The 10 selected criteria have been qualified through a comprehensive list of 36 criteria for practicality purposes, based on semi-structured experts' interviews and have been evaluated using qualitative variables.…”

Section: Decision Criteria and Alternativesmentioning

confidence: 99%

“…The same concept was extended by Kolios et al [17], where an extended version of TOPSIS is introduced, which takes into consideration the stochasticity of inputs, which is a common issue towards the successful implementation of MCDMs. With the same aim, Martin et al [21] presented a methodology to evaluate a number of floating support structure configurations, for offshore wind turbines deployed in deep waters. Doukas et al [22] used TOPSIS on energy policy objectives for sustainable development and renewable energy preferences, while Datta et al [23] identified the best islanding detection method for a solar photovoltaic system by using TOPSIS along with other MCDM methods.…”

Section: Introductionmentioning

confidence: 99%

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A Comparative Study of Multiple-Criteria Decision-Making Methods under Stochastic Inputs

et al. 2016

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This paper presents an application and extension of multiple-criteria decision-making (MCDM) methods to account for stochastic input variables. More in particular, a comparative study is carried out among well-known and widely-applied methods in MCDM, when applied to the reference problem of the selection of wind turbine support structures for a given deployment location. Along with data from industrial experts, six deterministic MCDM methods are studied, so as to determine the best alternative among the available options, assessed against selected criteria with a view toward assigning confidence levels to each option. Following an overview of the literature around MCDM problems, the best practice implementation of each method is presented aiming to assist stakeholders and decision-makers to support decisions in real-world applications, where many and often conflicting criteria are present within uncertain environments. The outcomes of this research highlight that more sophisticated methods, such as technique for the order of preference by similarity to the ideal solution (TOPSIS) and Preference Ranking Organization method for enrichment evaluation (PROMETHEE), better predict the optimum design alternative.

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Section: Decision Criteria and Alternativesmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

A Comparative Study of Multiple-Criteria Decision-Making Methods under Stochastic Inputs

et al. 2016

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“…[31]. There are also few contributions dealing with multi-criteria analysis of design options, for instance for wind turbine support structures [34,36]; and for hybrid energy systems [1].…”

Section: Ranking Phasementioning

confidence: 99%

A methodology for multi-criteria design of multi-use offshore platforms for marine renewable energy harvesting

et al. 2016

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a b s t r a c tMulti-use offshore platforms (MUPs) combining renewable energy from the sea, aquaculture and transportation facilities can be considered as a challenging way to boost blue growth and make renewable energy (especially wave energy) environmentally and socio-economically sustainable. MUPs allow sharing the financial and other market/non-market costs of installation and management, locally using the produced energy for different functionalities and optimizing marine spatial planning. The design of these solutions is a complex interdisciplinary challenge, involving scientists and technical experts with different backgrounds.This paper presents a new methodology for the design of a MUP based on technical, environmental, social and economic criteria. The methodology consists of four steps: a pre-screening phase, to assess the feasibility of different maritime uses at the site; a preliminary design of the alternative schemes based on the identified maritime uses; a ranking phase, where the performance of the MUPs is scored by means of expert judgment of the selected criteria; a preliminary design of the selected MUP selected.An example application of this procedure to a site offshore the Western Sardinia coast, Mediterranean Sea, Italy, is provided. In this site the deployment of a MUP consisting of wave energy converters, offshore wind turbines and aquaculture is specifically investigated.

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“…1. The choice of types of support structure depends on multiple criteria, such as water depth, seabed conditions and financial constraints [7][8][9][10][11]. Monopiles (see Fig.…”

Section: Introductionmentioning

confidence: 99%

Integrated structural optimisation of offshore wind turbine support structures based on finite element analysis and genetic algorithm

2017

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By accounting for almost 25% of the capital cost of an OWT (offshore wind turbine), optimisation of support structures provides an efficient way to reduce the currently high cost of offshore wind energy. In this paper, a structural optimisation model for OWT support structures has been developed based on a coupled parametric FEA (Finite Element Analysis) and GA (Genetic Algorithm), minimising the mass of the support structure under multi-criteria constraints. Contrary to existing optimisation models for OWT support structures, the proposed model is an integrated structural optimisation model, which optimises the components of the support structure (i.e. tower, transition piece, grout and monopile) simultaneously. The outer diameters and section thicknesses along the support structure are chosen as design variables. A set of constraints based on multi-criteria design assessment is applied according to standard requirements, which includes vibration, stress, deformation, buckling, fatigue and design variable constraints. The model has been applied to the NREL (National Renewable Energy Laboratory) 5MW OWT on an OC3 (Offshore Code Comparison Collaboration) monopile. The results of the application of the integrated optimisation methodology show a 19.8% reduction in the global mass of the support structure while satisfying all the design constraints. It is demonstrated that the proposed structural optimisation model is capable of effectively and accurately determining the optimal design of OWT support structures, which significantly improves their design efficiency.

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Application and extension of the TOPSIS method for the assessment of floating offshore wind turbine support structures

Cited by 33 publications

References 8 publications

A Comparative Study of Multiple-Criteria Decision-Making Methods under Stochastic Inputs

A Comparative Study of Multiple-Criteria Decision-Making Methods under Stochastic Inputs

A methodology for multi-criteria design of multi-use offshore platforms for marine renewable energy harvesting

Integrated structural optimisation of offshore wind turbine support structures based on finite element analysis and genetic algorithm

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