Development of an offshore specific wind power forecasting system / Melih Kurt
データ種別 | 電子ブック |
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出版情報 | Kassel : Kassel University Press , [2017] |
本文言語 | 英語 |
大きさ | 1 online resource : color illustrations |
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資料種別 | 機械可読データファイル |
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内容注記 | Front Cover Title Page Imprint Abstract (English) Abstract (German) Content List of figures List of tables Abbreviations Acknowledgement 1 Introduction and summary 1.1 Development of offshore wind energy 1.1.1 Offshore wind power in Europe 1.1.2 Offshore wind power world wide 1.1.3 Challenges of offshore wind energy 1.2 Motivation, objectives, problem statement and focus 1.2.1 Motivation 1.2.2 Problem statement 1.2.3 Purpose of the PhD work 1.2.4 Publications 1.2.5 Outline of the thesis and exhaustive summary2 State of the art in wind power forecasting 2.1 Application of wind power forecasting in energy trade in Germany 2.1.1 Persistence wind power forecasting 2.1.2 Short term wind power forecasting 2.1.3 Day-ahead wind power forecasting 2.2 Energy meteorology and numerical weather predictions 2.3 State of wind power forecasting methods and research 2.3.1 State of offshore wind power forecasting 2.3.2 Existing wind power forecasting methods 2.4 Existing applications for wind power forecasting 2.5 Summary3 Input data for development of forecasting models 3.1 Available data 3.2 Development of a plausibility check for meteorological parameters 3.2.1 Correction of measurements from FINO1 meteorological mast 3.2.2 Determination of wind sectors disturbed by the wind farm 3.2.3 Validation of FINO1 wind speed measurements 3.3 Plausibility of power data and detection of installed wind power 3.4 Assessment of the accuracy of wind power forecasting 3.5 Summary 4 Development and implementation of models for wind power forecasting 4.1 Development of a physical model based on power curve4.1.1 WAPPM Wake Adjusted Physical Power Model 4.1.2 Optimization of WAPPM with Model Output Statistics (MOS) 4.1.3 Simulation of the wind power time series of alpha ventus 4.2 Wind power forecasting using WAPPM 4.2.1 Physical model without considering wake effects 4.2.2 Physical model with consideration of wake effects 4.2.3 Adapted physical model 4.2.4 Physical model extended with model output statistics 4.3 Artificial neural networks in wind power forecasting 4.3.1 Application of artificial neural networks4.3.2 Variation of prediction error dependent on hidden neurons 4.4 Development of ensemble wind power forecast models 4.4.1 Ensemble physical wind power forecasting 4.4.2 Simple averaging of the predictions of different forecasting methods 4.4.3 Hybrid system 1 â#x80;#x93; WAPPM prediction as additional input to ANN 4.4.4 Hybrid system 2 â#x80;#x93; Double ANN 1 4.4.5 Hybrid system 3 â#x80;#x93; Double ANN 2 4.5 Summary 5 Consecutive selection of learning approach and physical model |
一般注記 | In English with abstract in English and German Open Access Includes bibliographical references Originally presented as the author's thesis (doctoral)--Universität Kassel, 2017 Online resource; title from PDF title page (EBSCO, viewed April 17, 2018) |
著者標目 | *Kurt, Melih, |
件 名 | BSH:Electronic books LCSH:Wind forecasting LCSH:Offshore wind power plants LCSH:Wind power BISACSH:SCIENCE -- Earth Sciences -- Geography 全ての件名で検索 BISACSH:SCIENCE -- Earth Sciences -- Geology 全ての件名で検索 FREE:Offshore wind power plants FREE:Wind forecasting FREE:Wind power |
分 類 | DC23:551.6418 |
書誌ID | ED00003780 |
ISBN | 9783737603478 |
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※2020年9月23日以降