- Standort
-
Deutsche Nationalbibliothek Frankfurt am Main
- Umfang
-
Online-Ressource
- Sprache
-
Englisch
- Anmerkungen
-
Stuttgart, Universität Stuttgart, Dissertation, 2021
- Schlagwort
-
Optical radar
Forecasting
Wind power
- Ereignis
-
Veröffentlichung
- (wo)
-
Stuttgart
- (wer)
-
Universitätsbibliothek der Universität Stuttgart
- (wann)
-
2022
- Urheber
- Beteiligte Personen und Organisationen
- DOI
-
10.18419/opus-12169
- URN
-
urn:nbn:de:bsz:93-opus-ds-121861
- Rechteinformation
-
Der Zugriff auf das Objekt ist unbeschränkt möglich.
- Letzte Aktualisierung
-
15.08.2025, 07:34 MESZ
Datenpartner
Dieses Objekt wird bereitgestellt von:
Deutsche Nationalbibliothek. Bei Fragen zum Objekt wenden Sie sich bitte an den Datenpartner.
Deutsche Nationalbibliothek. Bei Fragen zum Objekt wenden Sie sich bitte an den Datenpartner.
Beteiligte
- Würth, Ines
- Cheng, Po Wen
- Universitätsbibliothek der Universität Stuttgart
Entstanden
- 2022
Ähnliche Objekte (12)
Parameterization of Wind Evolution using Lidar
Parameterization of wind evolution using lidar
Flatness-based feedforward control of wind turbines using Lidar
Improved modeling of lidar wind preview for wind turbine control
Lidar-based wake tracking for closed-loop wind farm control
Evaluation of lidar-assisted wind turbine control under various turbulence characteristics
Application of a Monte Carlo procedure for probabilistic fatigue design of floating offshore wind turbines
Application of a Monte Carlo Procedure for Probabilistic Fatigue Design of Floating Offshore Wind Turbines
Comparison of feedforward and model predictive control of wind turbines using LIDAR
Correction of motion influence for nacelle based lidar systems on floating wind turbines
Machine learning based virtual load sensors for mooring lines using motion and lidar measurements
Reducing the uncertainty of lidar measurements in complex terrain using a linear model approach
Parameterization of Wind Evolution using Lidar
Parameterization of wind evolution using lidar
Flatness-based feedforward control of wind turbines using Lidar
Improved modeling of lidar wind preview for wind turbine control
Lidar-based wake tracking for closed-loop wind farm control
Evaluation of lidar-assisted wind turbine control under various turbulence characteristics
Application of a Monte Carlo procedure for probabilistic fatigue design of floating offshore wind turbines
Application of a Monte Carlo Procedure for Probabilistic Fatigue Design of Floating Offshore Wind Turbines
Comparison of feedforward and model predictive control of wind turbines using LIDAR
Correction of motion influence for nacelle based lidar systems on floating wind turbines
Machine learning based virtual load sensors for mooring lines using motion and lidar measurements
Reducing the uncertainty of lidar measurements in complex terrain using a linear model approach
Parameterization of Wind Evolution using Lidar
Parameterization of wind evolution using lidar
Flatness-based feedforward control of wind turbines using Lidar
Improved modeling of lidar wind preview for wind turbine control
Lidar-based wake tracking for closed-loop wind farm control
Evaluation of lidar-assisted wind turbine control under various turbulence characteristics
Application of a Monte Carlo procedure for probabilistic fatigue design of floating offshore wind turbines
Application of a Monte Carlo Procedure for Probabilistic Fatigue Design of Floating Offshore Wind Turbines
Comparison of feedforward and model predictive control of wind turbines using LIDAR
Correction of motion influence for nacelle based lidar systems on floating wind turbines
Machine learning based virtual load sensors for mooring lines using motion and lidar measurements