Artikel
DIETERpy: A Python framework for the Dispatch and Investment Evaluation Tool with Endogenous Renewables
DIETER is an open-source power sector model designed to analyze future settings with very high shares of variable renewable energy sources. It minimizes overall system costs, including fixed and variable costs of various generation, flexibility and sector coupling options. Here we introduce DIETERpy that builds on the existing model version, written in the General Algebraic Modeling System (GAMS), and enhances it with a Python framework. This combines the flexibility of Python regarding pre- and post-processing of data with a straightforward algebraic formulation in GAMS and the use of efficient solvers. DIETERpy also offers a browser-based graphical user interface. The new framework is designed to be easily accessible as it enables users to run the model, alter its configuration, and define numerous scenarios without a deeper knowledge of GAMS. Code, data, and manuals are available in public repositories under permissive licenses for transparency and reproducibility.
- Sprache
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Englisch
- Erschienen in
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Journal: SoftwareX ; ISSN: 2352-7110 ; Volume: 15 ; Year: 2021 ; Amsterdam: Elsevier BV
- Klassifikation
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Wirtschaft
- Thema
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Power sector modeling
Open-source modeling
GAMS
Python
Energy storage
Flexibility options
Sector coupling
Renewable energy integration
- Ereignis
-
Geistige Schöpfung
- (wer)
-
Gaete-Morales, Carlos
Kittel, Martin
Roth, Alexander
Schill, Wolf-Peter
- Ereignis
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Veröffentlichung
- (wer)
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Elsevier BV
- (wo)
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Amsterdam
- (wann)
-
2021
- DOI
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doi:10.1016/j.softx.2021.100784
- Handle
- Letzte Aktualisierung
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10.03.2025, 11:43 MEZ
Datenpartner
Dieses Objekt wird bereitgestellt von:
ZBW - Deutsche Zentralbibliothek für Wirtschaftswissenschaften - Leibniz-Informationszentrum Wirtschaft. Bei Fragen zum Objekt wenden Sie sich bitte an den Datenpartner.
ZBW - Deutsche Zentralbibliothek für Wirtschaftswissenschaften - Leibniz-Informationszentrum Wirtschaft. Bei Fragen zum Objekt wenden Sie sich bitte an den Datenpartner.
Objekttyp
- Artikel
Beteiligte
- Gaete-Morales, Carlos
- Kittel, Martin
- Roth, Alexander
- Schill, Wolf-Peter
- Elsevier BV
Entstanden
- 2021
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