Abstract

The paper describes how Data Packages can be used for creating reproducible workflows in energy system modeling. The presented concept has been implemented in the Python package oemof.tabular. The package is designed as an interface to instantiate energy system models from tabular data sources based on the oemof.solph library. To implement the data model, oemof.tabular extends the Open Energy Modelling Framework (oemof) by facada classes. The developed data model allows users to work with Data Packages and meta data information. The simplified tabular data structure can be used for large energy system models as well as in teaching environments leveraging functionalities of the already widely used oemof.solph library.

Highlights

  • Analyses of future energy systems are based on tools for complex socio-techno-economic systems

  • A trend towards open source energy models can be observed in the energy system modeling research field [15], as models have been criticized for lack of transparency and reproducibility [17]

  • This paper introduces the application of the facade concept and the usage of Data Packages for the Open Energy System Modeling Framework

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Summary

INTRODUCTION

Analyses of future energy systems are based on tools for complex socio-techno-economic systems The complexity of these systems increases due to the intermittent supply characteristics of renewable energies which require high temporal and spatial resolution modeling. Data handling including input collection, processing and result analysis is one of the most time-consuming tasks. The decision about how to create the required data sets from raw data sources and the post-processing of result data is often left to the user. Due to these two reasons, re-use of data and more importantly reproducibility of model results is a challenging task, even for experienced modelers. The concept is not restricted to this package, but can be applied with other software as well

BACKGROUND
FACADES
DATA PACKAGES
REPRODUCIBLE WORKFLOWS
CONCLUSION
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