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

TL;DR

DIETERpy is an accessible Python-based framework that enhances the existing DIETER power sector model, allowing easier scenario analysis and user interaction for high renewable energy system planning.

Contribution

It introduces a Python framework for DIETER, improving usability, flexibility, and accessibility, with a graphical interface and open-source resources.

Findings

Enables scenario analysis with high renewable shares

Provides a user-friendly graphical interface

Ensures transparency through open-source code and data

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.