{"title":"基于蒙特卡罗和稀疏网格的海上风电场不确定性量化","authors":"P. Richter, J. Wolters, Martin Frank","doi":"10.1080/15567249.2021.2000520","DOIUrl":null,"url":null,"abstract":"ABSTRACT The power produced by an offshore wind farm is subject to multiple uncertainties, such as volatile wind, turbine performance wear, and availability losses. Knowledge about the propagation of these uncertainties and their effect on the produced power is crucial in the design stage of a wind farm. Due to the multitude of uncertainties, an analysis requires high-dimensional numerical integration to determine these parameter sensitivities. Such an analysis has not been done in the current literature for the full set of parameters. In this work, a thorough analysis of all uncertainties is provided, modeled from several years of collected data from the existing wind farms Horns Rev 1, DanTysk, and Sandbank. The analysis reveals four major parameters, allowing the other parameters to be neglected in future measurement data acquisitions and sensitivity analysis processes. Furthermore, the accuracy of several Uncertainty Quantification techniques is analyzed and a recommendation for future analysis is given.","PeriodicalId":51247,"journal":{"name":"Energy Sources Part B-Economics Planning and Policy","volume":null,"pages":null},"PeriodicalIF":3.1000,"publicationDate":"2021-12-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"10","resultStr":"{\"title\":\"Uncertainty quantification of offshore wind farms using Monte Carlo and sparse grid\",\"authors\":\"P. Richter, J. Wolters, Martin Frank\",\"doi\":\"10.1080/15567249.2021.2000520\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"ABSTRACT The power produced by an offshore wind farm is subject to multiple uncertainties, such as volatile wind, turbine performance wear, and availability losses. Knowledge about the propagation of these uncertainties and their effect on the produced power is crucial in the design stage of a wind farm. Due to the multitude of uncertainties, an analysis requires high-dimensional numerical integration to determine these parameter sensitivities. Such an analysis has not been done in the current literature for the full set of parameters. In this work, a thorough analysis of all uncertainties is provided, modeled from several years of collected data from the existing wind farms Horns Rev 1, DanTysk, and Sandbank. The analysis reveals four major parameters, allowing the other parameters to be neglected in future measurement data acquisitions and sensitivity analysis processes. Furthermore, the accuracy of several Uncertainty Quantification techniques is analyzed and a recommendation for future analysis is given.\",\"PeriodicalId\":51247,\"journal\":{\"name\":\"Energy Sources Part B-Economics Planning and Policy\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":3.1000,\"publicationDate\":\"2021-12-11\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"10\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Energy Sources Part B-Economics Planning and Policy\",\"FirstCategoryId\":\"5\",\"ListUrlMain\":\"https://doi.org/10.1080/15567249.2021.2000520\",\"RegionNum\":4,\"RegionCategory\":\"工程技术\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q3\",\"JCRName\":\"ENERGY & FUELS\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Energy Sources Part B-Economics Planning and Policy","FirstCategoryId":"5","ListUrlMain":"https://doi.org/10.1080/15567249.2021.2000520","RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"ENERGY & FUELS","Score":null,"Total":0}
Uncertainty quantification of offshore wind farms using Monte Carlo and sparse grid
ABSTRACT The power produced by an offshore wind farm is subject to multiple uncertainties, such as volatile wind, turbine performance wear, and availability losses. Knowledge about the propagation of these uncertainties and their effect on the produced power is crucial in the design stage of a wind farm. Due to the multitude of uncertainties, an analysis requires high-dimensional numerical integration to determine these parameter sensitivities. Such an analysis has not been done in the current literature for the full set of parameters. In this work, a thorough analysis of all uncertainties is provided, modeled from several years of collected data from the existing wind farms Horns Rev 1, DanTysk, and Sandbank. The analysis reveals four major parameters, allowing the other parameters to be neglected in future measurement data acquisitions and sensitivity analysis processes. Furthermore, the accuracy of several Uncertainty Quantification techniques is analyzed and a recommendation for future analysis is given.
期刊介绍:
12 issues per year
Abstracted and/or indexed in: Applied Science & Technology Index; API Abstracts/Literature; Automatic Subject Index Citation; BIOSIS Previews; Cabell’s Directory of Publishing Opportunities in Economics and Finance; Chemical Abstracts; CSA Aquatic Science & Fisheries Abstracts; CSA Environmental Sciences & Pollution Management Database; CSA Pollution Abstracts; Current Contents/Engineering, Technology & Applied Sciences; Directory of Industry Data Sources; Economic Abstracts; Electrical and Electronics Abstracts; Energy Information Abstracts; Energy Research Abstracts; Engineering Index Monthly; Environmental Abstracts; Environmental Periodicals Bibliography (EPB); International Abstracts in Operations Research; Operations/Research/Management Science Abstracts; Petroleum Abstracts; Physikalische Berichte; and Science Citation Index.
Taylor & Francis make every effort to ensure the accuracy of all the information (the "Content") contained in our publications. However, Taylor & Francis, our agents, and our licensors make no representations or warranties whatsoever as to the accuracy, completeness, or suitability for any purpose of the Content. Any opinions and views expressed in this publication are the opinions and views of the authors, and are not the views of or endorsed by Taylor & Francis. The accuracy of the Content should not be relied upon and should be independently verified with primary sources of information. Taylor & Francis shall not be liable for any losses, actions, claims, proceedings, demands, costs, expenses, damages, and other liabilities whatsoever or howsoever caused arising directly or indirectly in connection with, in relation to, or arising out of the use of the Content. Terms & Conditions of access and use can be found at http://www.tandfonline.com/page/terms-and-conditions .