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Institute for Data and Process Science

A Computationally Efficient End-to-End Learning Approach for Smart Energy Storage Systems

Autoren

Ulrich Ludolfinger
Ulrich.Ludolfinger@haw-landshut.de
Thomas Hamacher
Prof. Dr. Maren Martens
Maren.Martens@haw-landshut.de

Medien

2025 IEEE PES Innovative Smart Grid Technologies Europe (ISGT EUROPE). Conference Proceedings.

Veröffentlichungsjahr

2025

Band

2025

Seiten

1-5

Veröffentlichungsart

Konferenzbeitrag (peer reviewed)

Forschungsprojekt

ReLLFloW

DOI

https://doi.org/10.1109/ISGTEurope64741.2025.11305630

Zitierung

Ludolfinger, Ulrich; Hamacher, Thomas; Martens, Maren (2025): A Computationally Efficient End-to-End Learning Approach for Smart Energy Storage Systems. 2025 IEEE PES Innovative Smart Grid Technologies Europe (ISGT EUROPE). Conference Proceedings. 2025, 1-5. DOI: 10.1109/ISGTEurope64741.2025.11305630

Peer Reviewed

Ja

Institute for Data and Process Science

A Computationally Efficient End-to-End Learning Approach for Smart Energy Storage Systems