Wind turbine power curve modeling using maximum likelihood estimation method
DC Field | Value | Language |
---|---|---|
dc.contributor.author | Seo, Seokho | - |
dc.contributor.author | Oh, Si-Doek | - |
dc.contributor.author | Kwak, Ho-Young | - |
dc.date.accessioned | 2021-06-18T07:28:11Z | - |
dc.date.available | 2021-06-18T07:28:11Z | - |
dc.date.issued | 2019-06 | - |
dc.identifier.issn | 0960-1481 | - |
dc.identifier.uri | https://scholarworks.bwise.kr/cau/handle/2019.sw.cau/44802 | - |
dc.description.abstract | Modeling of wind turbine power curve which shows the relationship between wind speed and its power output can be used as an important tool in monitoring and forecasting wind energy. A data-driven approach to find most probable probability distribution function (PDF) for wind speed and turbine power is presented in this study. Equations for the scale and shape parameters in the Weibull wind speed distribution and equations for the four parameters in the logistic function were obtained explicitly by maximum likelihood estimation (MLE) method. With help of a selected data set from the wind speed and the corresponding power output data which was collected over a period of a year, the values of the parameters were obtained by solving the equations by iteration procedures. The predicted powers by the obtained logistic function closely follow the measured turbine powers averaged at 5-min or 10-min. Monitoring turbine power output by the logistic function was also tested for the measured powers in other time duration. (C) 2018 Elsevier Ltd. All rights reserved. | - |
dc.format.extent | 6 | - |
dc.language | 영어 | - |
dc.language.iso | ENG | - |
dc.publisher | PERGAMON-ELSEVIER SCIENCE LTD | - |
dc.title | Wind turbine power curve modeling using maximum likelihood estimation method | - |
dc.type | Article | - |
dc.identifier.doi | 10.1016/j.renene.2018.09.087 | - |
dc.identifier.bibliographicCitation | RENEWABLE ENERGY, v.136, pp 1164 - 1169 | - |
dc.description.isOpenAccess | N | - |
dc.identifier.wosid | 000460847800101 | - |
dc.identifier.scopusid | 2-s2.0-85062145856 | - |
dc.citation.endPage | 1169 | - |
dc.citation.startPage | 1164 | - |
dc.citation.title | RENEWABLE ENERGY | - |
dc.citation.volume | 136 | - |
dc.type.docType | Article | - |
dc.publisher.location | 영국 | - |
dc.subject.keywordAuthor | Logistic function | - |
dc.subject.keywordAuthor | Wind turbine power curve | - |
dc.subject.keywordAuthor | Weibull distribution | - |
dc.subject.keywordAuthor | Maximum likelihood estimation method | - |
dc.subject.keywordPlus | TUTORIAL | - |
dc.relation.journalResearchArea | Science & Technology - Other Topics | - |
dc.relation.journalResearchArea | Energy & Fuels | - |
dc.relation.journalWebOfScienceCategory | Green & Sustainable Science & Technology | - |
dc.relation.journalWebOfScienceCategory | Energy & Fuels | - |
dc.description.journalRegisteredClass | scie | - |
dc.description.journalRegisteredClass | scopus | - |
Items in ScholarWorks are protected by copyright, with all rights reserved, unless otherwise indicated.
84, Heukseok-ro, Dongjak-gu, Seoul, Republic of Korea (06974)02-820-6194
COPYRIGHT 2019 Chung-Ang University All Rights Reserved.
Certain data included herein are derived from the © Web of Science of Clarivate Analytics. All rights reserved.
You may not copy or re-distribute this material in whole or in part without the prior written consent of Clarivate Analytics.