Applying modeling, simulation and machine learning for the renewable energy transition
- Location
-
Deutsche Nationalbibliothek Frankfurt am Main
- Extent
-
Online-Ressource
- Language
-
Englisch
- Notes
-
Berlin, Technische Universität Berlin, Dissertation, 2023
- Classification
-
Natürliche Ressourcen, Energie und Umwelt
- Keyword
-
Netzstabilität
Dezentrale Elektrizitätserzeugung
Erneuerbare Energien
Elektrizitätsversorgungsnetz
Komplexes System
- Event
-
Veröffentlichung
- (where)
-
Berlin
- (who)
-
Technische Universität Berlin
- (when)
-
2023
- Creator
- Contributor
-
Schöll, Eckehard
Hellmann, Frank
Lüdge, Kathy
Boers, Niklas
Schöll, Eckehard
- DOI
-
10.14279/depositonce-18257
- Handle
-
11303/19460
- URN
-
urn:nbn:de:101:1-2023080207131221781400
- Rights
-
Der Zugriff auf das Objekt ist unbeschränkt möglich.
- Last update
-
25.03.2025, 1:53 PM CET
Data provider
This object is provided by:
Deutsche Nationalbibliothek. If you have any questions about the object, please contact the data provider.
Deutsche Nationalbibliothek. If you have any questions about the object, please contact the data provider.
Associated
- Lindner, Michael
- Schöll, Eckehard
- Hellmann, Frank
- Lüdge, Kathy
- Boers, Niklas
- Technische Universität Berlin
Time of origin
- 2023
Other Objects (12)
Machine intelligence for the renewable energy transition : prediction, inference, and policy advice
The Transition to Renewable Energy
Transition to renewable energy systems
Mapping glacier basal sliding applying machine learning
Electricity Storage and the Renewable Energy Transition
Electricity Storage and the Renewable Energy Transition
100% renewable energy transition: Pathways and implementation
Electricity Storage and the Renewable Energy Transition
Automated gene function prediction : applying ontology and machine learning
Applying Meta-modeling for extended CGE-modeling: Sampling techniques and potential application
Applying meta-modeling for extended CGE-modeling: Sampling techniques and potential application
Applying machine learning to derive actionable insights in precision oncology
Machine intelligence for the renewable energy transition : prediction, inference, and policy advice
The Transition to Renewable Energy
Transition to renewable energy systems
Mapping glacier basal sliding applying machine learning
Electricity Storage and the Renewable Energy Transition
Electricity Storage and the Renewable Energy Transition
100% renewable energy transition: Pathways and implementation
Electricity Storage and the Renewable Energy Transition
Automated gene function prediction : applying ontology and machine learning
Applying Meta-modeling for extended CGE-modeling: Sampling techniques and potential application
Applying meta-modeling for extended CGE-modeling: Sampling techniques and potential application
Applying machine learning to derive actionable insights in precision oncology
Machine intelligence for the renewable energy transition : prediction, inference, and policy advice
The Transition to Renewable Energy
Transition to renewable energy systems
Mapping glacier basal sliding applying machine learning
Electricity Storage and the Renewable Energy Transition
Electricity Storage and the Renewable Energy Transition
100% renewable energy transition: Pathways and implementation
Electricity Storage and the Renewable Energy Transition
Automated gene function prediction : applying ontology and machine learning
Applying Meta-modeling for extended CGE-modeling: Sampling techniques and potential application
Applying meta-modeling for extended CGE-modeling: Sampling techniques and potential application