Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/102863
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dc.contributorDepartment of Building Environment and Energy Engineeringen_US
dc.creatorSun, Hen_US
dc.creatorYang, Hen_US
dc.date.accessioned2023-11-17T02:58:16Z-
dc.date.available2023-11-17T02:58:16Z-
dc.identifier.issn0960-1481en_US
dc.identifier.urihttp://hdl.handle.net/10397/102863-
dc.language.isoenen_US
dc.publisherPergamon Pressen_US
dc.rights© 2019 Elsevier Ltd. All rights reserved.en_US
dc.rights© 2019. This manuscript version is made available under the CC-BY-NC-ND 4.0 license https://creativecommons.org/licenses/by-nc-nd/4.0/.en_US
dc.rightsThe following publication Sun, H., & Yang, H. (2020). Numerical investigation of the average wind speed of a single wind turbine and development of a novel three-dimensional multiple wind turbine wake model. Renewable Energy, 147, 192-203 is available at https://doi.org/10.1016/j.renene.2019.08.122.en_US
dc.subjectAverage wind speeden_US
dc.subjectThree-dimensional multiple wake modelen_US
dc.subjectValidation by wind tunnel experimentsen_US
dc.subjectWake distribution predictionen_US
dc.titleNumerical investigation of the average wind speed of a single wind turbine and development of a novel three-dimensional multiple wind turbine wake modelen_US
dc.typeJournal/Magazine Articleen_US
dc.identifier.spage192en_US
dc.identifier.epage203en_US
dc.identifier.volume147en_US
dc.identifier.issuePart 1en_US
dc.identifier.doi10.1016/j.renene.2019.08.122en_US
dcterms.abstractThis paper reports the newly developed three-dimensional analytical wake models for single and multiple wind turbines. Firstly, the average wind speed of a single wind turbine is studied based on the single wake model. For a single wind turbine, assuming the incoming wind is distributed as power law in the vertical direction, the average wind speeds have a close relationship to the power exponent α, the hub height h0 and the rotor radius r0. When α=0.4, the average wind speed can decrease to 96% of the speed at the hub height. Secondly, the three-dimensional multiple wake model is developed based on the single wake model. The method of Sum of Squares is applied to solve the wake adding problem. The available wind tunnel experimental data of two different layouts are used to validate the wake model. At the three representative heights, the wake model predicts the distribution of wind speed accurately. For Layout 1, at the hub and the top heights, most of the relative errors between the wake model results and the experimental data are smaller than 6%. At the top height, all relative errors are smaller than 20%. For Layout 2, the largest errors of the wake model are 8.5% at the top height, 17.8% at the bottom height and 21.2% at the hub height. The results predicted by the multiple wake model are demonstrated as well. The presented wake model can be used to describe the wind distribution and optimize the layout of wind farm.en_US
dcterms.accessRightsopen accessen_US
dcterms.bibliographicCitationRenewable energy, Mar. 2020, v. 147, pt. 1, p. 192-203en_US
dcterms.isPartOfRenewable energyen_US
dcterms.issued2020-03-
dc.identifier.scopus2-s2.0-85071631279-
dc.identifier.eissn1879-0682en_US
dc.description.validate202311 bckwen_US
dc.description.oaAccepted Manuscripten_US
dc.identifier.FolderNumberBEEE-0275-
dc.description.fundingSourceOthersen_US
dc.description.fundingTextThe Hong Kong Polytechnic Universityen_US
dc.description.pubStatusPublisheden_US
dc.identifier.OPUS15598153-
dc.description.oaCategoryGreen (AAM)en_US
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