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Dokumenttyp:
Forschungsdaten
Veröffentlichungsdatum:
14.04.2022
Verantwortlich:
Collath, Nils
Autorinnen / Autoren:
Collath, Nils; Tepe, Benedikt; Englberger, Stefan; Jossen, Andreas; Hesse, Holger
Institutionszugehörigkeit:
TUM
Herausgeber:
TUM
Titel:
Battery degradation in BESS use-cases with varying degradation models and stress factor assumptions
Identifikator:
doi:10.14459/2022mp1652796
Enddatum der Datenerzeugung:
25.03.2022
Fachgebiet:
ELT Elektrotechnik; TEC Technik, Ingenieurwissenschaften (allgemein)
Quellen der Daten:
Simulationen / simulations
Datentyp:
Programme und Anwendungen / software and applications
Methode der Datenerhebung:
Time-series simulations with the above mentioned adapted version of the software “SimSES”. The original repository of SimSES is accessible under the below link: https://gitlab.lrz.de/open-ees-ses/simses

Beschreibung:
This public dataset contains an adapted version of the time-series simulation tool “SimSES”, as used in an associated publication. Furthermore, results of the time-series simulation for two different degradation models ("NMC Schmalstieg" and "LFP Naumann") and three key applications of battery energy storage systems are included in this dataset (Frequency Containment Reserve, Peak Shaving and Self Consumption Increase with a home storage system). The results include scenarios in which individual...     »
Schlagworte:
Degradation model, lithium-ion, battery energy storage system, SimSES, time-series simulation, stress factor
Technische Hinweise:
View and download (22 GB total, 1755 Files)
The data server also offers downloads with FTP
The data server also offers downloads with rsync (password m1652796):
rsync rsync://m1652796@dataserv.ub.tum.de/m1652796/
Sprache:
en
Andere Rechte:

Simulation Results: Creative Commons Attribution 4.0 International (CC BY 4.0) https://creativecommons.org/licenses/by/4.0/

Software (adapted version of SimSES): BSD 3-Clause License: https://opensource.org/licenses/BSD-3-Clause

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