Wind turbine selection method based on the statistical analysis of nominal specifications for estimating the cost of energy

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dc.citation.journalTitleAPPLIED ENERGYspa
dc.contributor.authorArias-Rosales, A.
dc.contributor.authorOsorio-Gómez, G.
dc.contributor.departmentUniversidad EAFIT. Departamento de Ingeniería de Diseño
dc.contributor.researchgroupIngeniería de Diseño (GRID)spa
dc.date.accessioned2021-04-12T21:15:02Z
dc.date.available2021-04-12T21:15:02Z
dc.date.issued2018-10-15
dc.description.abstractWind turbine selection is a critical engineering problem in the overall cost-effectiveness of a wind project. With the wide spreading and democratization of wind energy technologies, non-expert stakeholders are being faced with the challenge of selecting among very different wind turbines. As a comprehensive indicator, the cost of energy can serve as a guide, but reportedly misleading publicity and commonly unavailable information render its calculation more inaccessible and less reliable. Accordingly, this work proposes a method to compare wind turbines, on the basis of the cost of energy, from only nominal specifications and a standard characterization of the local wind conditions. For this endeavor, it was identified that two key variables are not usually available at a preliminary stage: the total efficiency and a feasible hub height. Through a systematic statistical analysis of the trends in a constructed dataset of 176 turbines, it was possible to establish regression models for the estimation of both variables. These models were tested in a validation set and their estimations were found to correctly characterize the central trend of the data without significant deviations. The uncertainty related to the use of both models was addressed by analyzing the 95% Prediction Intervals and the stochastic rank dominance. The established statistical models were then used as the core of the proposed selection method. When the available information is limited or not trustworthy, the steps of the method can be followed as an approach to estimate the cost of energy of a given horizontal axis wind turbine in a given location. © 2018 Elsevier Ltdeng
dc.identifierhttps://eafit.fundanetsuite.com/Publicaciones/ProdCientif/PublicacionFrw.aspx?id=8200
dc.identifier.doi10.1016/j.apenergy.2018.06.103
dc.identifier.issn3062619
dc.identifier.issn18729118
dc.identifier.otherWOS;000447479400079
dc.identifier.otherSCOPUS;2-s2.0-85049472253
dc.identifier.urihttp://hdl.handle.net/10784/28991
dc.language.isoengeng
dc.publisherElsevier Ltd
dc.relationDOI;10.1016/j.apenergy.2018.06.103
dc.relationWOS;000447479400079
dc.relationSCOPUS;2-s2.0-85049472253
dc.relation.urihttps://www.scopus.com/inward/record.uri?eid=2-s2.0-85049472253&doi=10.1016%2fj.apenergy.2018.06.103&partnerID=40&md5=b7f8808a59d49343099e16c86fe3c057
dc.rightshttps://v2.sherpa.ac.uk/id/publication/issn/0306-2619
dc.sourceAPPLIED ENERGY
dc.subject.keywordCost benefit analysiseng
dc.subject.keywordCost effectivenesseng
dc.subject.keywordCost engineeringeng
dc.subject.keywordCost estimatingeng
dc.subject.keywordEstimationeng
dc.subject.keywordRegression analysiseng
dc.subject.keywordSpecificationseng
dc.subject.keywordStochastic modelseng
dc.subject.keywordStochastic systemseng
dc.subject.keywordUncertainty analysiseng
dc.subject.keywordWind powereng
dc.subject.keywordCost of energieseng
dc.subject.keywordEngineering problemseng
dc.subject.keywordHAWT dataseteng
dc.subject.keywordHorizontal axis wind turbineseng
dc.subject.keywordPrediction intervaleng
dc.subject.keywordSelection methodseng
dc.subject.keywordStatistical modelingeng
dc.subject.keywordWind energy technologyeng
dc.subject.keywordWind turbineseng
dc.subject.keywordcost analysiseng
dc.subject.keyworddata seteng
dc.subject.keyworddemocratizationeng
dc.subject.keywordestimation methodeng
dc.subject.keywordmodel validationeng
dc.subject.keywordnumerical methodeng
dc.subject.keywordstatistical analysiseng
dc.subject.keywordstochasticityeng
dc.subject.keywordwind powereng
dc.subject.keywordwind turbineeng
dc.titleWind turbine selection method based on the statistical analysis of nominal specifications for estimating the cost of energyeng
dc.typeinfo:eu-repo/semantics/articleeng
dc.typearticleeng
dc.typeinfo:eu-repo/semantics/publishedVersioneng
dc.typepublishedVersioneng
dc.type.localArtículospa

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