Development of an offshore specific wind power forecasting system:
Gespeichert in:
| 1. Verfasser: | |
|---|---|
| Format: | Elektronisch E-Book |
| Sprache: | English |
| Veröffentlicht: |
Kassel
Kassel University Press
[2017]
|
| Schlagworte: | |
| Online-Zugang: | kostenfrei |
| Beschreibung: | Originally presented as the author's thesis (doctoral)--Universität Kassel, 2017 |
| Beschreibung: | 1 Online-Ressource color illustrations |
| ISBN: | 3737603472 9783737603478 |
| Zugangseinschränkungen: | Open Access |
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| 505 | 8 | |a 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 | |
| 505 | 8 | |a 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 | |
| 505 | 8 | |a 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 | |
| 505 | 8 | |a 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 | |
| 505 | 8 | |a 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 | |
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| 650 | 4 | |a Wind power | |
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| 776 | 0 | 8 | |i Erscheint auch als |n Druck-Ausgabe |a Kurt, Melih |t Development of an offshore specific wind power forecasting system |d Kassel, [Germany] : kassel university press GmbH, ©2017 |h xvi, 182 pages |z 9783737603461 |
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| contents | 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 |
| ctrlnum | (OCoLC)1007700766 (DE-599)BVBBV048279181 |
| discipline | Elektrotechnik / Elektronik / Nachrichtentechnik Energietechnik |
| discipline_str_mv | Elektrotechnik / Elektronik / Nachrichtentechnik Energietechnik |
| format | Electronic eBook |
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| index_date | 2024-07-03T20:00:49Z |
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| owner_facet | DE-355 DE-BY-UBR |
| physical | 1 Online-Ressource color illustrations |
| psigel | ZDB-4-EOAC |
| publishDate | 2017 |
| publishDateSearch | 2017 |
| publishDateSort | 2017 |
| publisher | Kassel University Press |
| record_format | marc |
| spelling | Kurt, Melih Verfasser aut Development of an offshore specific wind power forecasting system Melih Kurt Kassel Kassel University Press [2017] 1 Online-Ressource color illustrations txt rdacontent c rdamedia cr rdacarrier Originally presented as the author's thesis (doctoral)--Universität Kassel, 2017 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 Open Access EbpS In English with abstract in English and German Centrales éoliennes en mer Énergie éolienne Vents Prévision Offshore wind power plants SCIENCE Earth Sciences Wind forecasting wind power Wind power Offshorebauwerk (DE-588)4128556-6 gnd rswk-swf Prognosemodell (DE-588)4125215-9 gnd rswk-swf Netzbetrieb (DE-588)4171506-8 gnd rswk-swf Windpark (DE-588)4543294-6 gnd rswk-swf Prognosequalität (DE-588)4115643-2 gnd rswk-swf Versorgungssicherheit (DE-588)7839944-0 gnd rswk-swf Elektrizitätseinspeisung (DE-588)4259675-0 gnd rswk-swf Windklima (DE-588)4461756-2 gnd rswk-swf Windenergie (DE-588)4079329-1 gnd rswk-swf Europa (DE-588)4015701-5 gnd rswk-swf Electronic books (DE-588)4113937-9 Hochschulschrift gnd-content Europa (DE-588)4015701-5 g Windpark (DE-588)4543294-6 s Offshorebauwerk (DE-588)4128556-6 s Windenergie (DE-588)4079329-1 s Elektrizitätseinspeisung (DE-588)4259675-0 s Netzbetrieb (DE-588)4171506-8 s Versorgungssicherheit (DE-588)7839944-0 s Windklima (DE-588)4461756-2 s Prognosemodell (DE-588)4125215-9 s Prognosequalität (DE-588)4115643-2 s DE-604 Erscheint auch als Druck-Ausgabe Kurt, Melih Development of an offshore specific wind power forecasting system Kassel, [Germany] : kassel university press GmbH, ©2017 xvi, 182 pages 9783737603461 https://search.ebscohost.com/login.aspx?direct=true&scope=site&db=nlebk&AN=1619744 Verlag kostenfrei Volltext |
| spellingShingle | Kurt, Melih Development of an offshore specific wind power forecasting system 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 Centrales éoliennes en mer Énergie éolienne Vents Prévision Offshore wind power plants SCIENCE Earth Sciences Wind forecasting wind power Wind power Offshorebauwerk (DE-588)4128556-6 gnd Prognosemodell (DE-588)4125215-9 gnd Netzbetrieb (DE-588)4171506-8 gnd Windpark (DE-588)4543294-6 gnd Prognosequalität (DE-588)4115643-2 gnd Versorgungssicherheit (DE-588)7839944-0 gnd Elektrizitätseinspeisung (DE-588)4259675-0 gnd Windklima (DE-588)4461756-2 gnd Windenergie (DE-588)4079329-1 gnd |
| subject_GND | (DE-588)4128556-6 (DE-588)4125215-9 (DE-588)4171506-8 (DE-588)4543294-6 (DE-588)4115643-2 (DE-588)7839944-0 (DE-588)4259675-0 (DE-588)4461756-2 (DE-588)4079329-1 (DE-588)4015701-5 (DE-588)4113937-9 |
| title | Development of an offshore specific wind power forecasting system |
| title_auth | Development of an offshore specific wind power forecasting system |
| title_exact_search | Development of an offshore specific wind power forecasting system |
| title_exact_search_txtP | Development of an offshore specific wind power forecasting system |
| title_full | Development of an offshore specific wind power forecasting system Melih Kurt |
| title_fullStr | Development of an offshore specific wind power forecasting system Melih Kurt |
| title_full_unstemmed | Development of an offshore specific wind power forecasting system Melih Kurt |
| title_short | Development of an offshore specific wind power forecasting system |
| title_sort | development of an offshore specific wind power forecasting system |
| topic | Centrales éoliennes en mer Énergie éolienne Vents Prévision Offshore wind power plants SCIENCE Earth Sciences Wind forecasting wind power Wind power Offshorebauwerk (DE-588)4128556-6 gnd Prognosemodell (DE-588)4125215-9 gnd Netzbetrieb (DE-588)4171506-8 gnd Windpark (DE-588)4543294-6 gnd Prognosequalität (DE-588)4115643-2 gnd Versorgungssicherheit (DE-588)7839944-0 gnd Elektrizitätseinspeisung (DE-588)4259675-0 gnd Windklima (DE-588)4461756-2 gnd Windenergie (DE-588)4079329-1 gnd |
| topic_facet | Centrales éoliennes en mer Énergie éolienne Vents Offshore wind power plants SCIENCE Wind forecasting wind power Wind power Offshorebauwerk Prognosemodell Netzbetrieb Windpark Prognosequalität Versorgungssicherheit Elektrizitätseinspeisung Windklima Windenergie Europa Hochschulschrift |
| url | https://search.ebscohost.com/login.aspx?direct=true&scope=site&db=nlebk&AN=1619744 |
| work_keys_str_mv | AT kurtmelih developmentofanoffshorespecificwindpowerforecastingsystem |