DIETERpy: a Python framework for The Dispatch and Investment Evaluation Tool with Endogenous Renewables

• URL: http://arxiv.org/abs/2010.00883v2
• Date: Wed, 7 Apr 2021 14:18:58 GMT
• Title: DIETERpy: a Python framework for The Dispatch and Investment Evaluation Tool with Endogenous Renewables
• Authors: Carlos Gaete-Morales, Martin Kittel, Alexander Roth and Wolf-Peter Schill
• Abstract summary: 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. 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.
• Score: 62.997667081978825
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: 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.

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