Preprint Article Version 1 Preserved in Portico This version is not peer-reviewed

The Open Energy Modelling Framework (oemof) - A novel approach in energy system modelling

Simon Hilpert
* ORCID logo ,
Cord Kaldemeyer
,
Uwe Krien
,
Stephan Günther
,
Clemens Wingenbach
,
Guido Plessmann
Version 1 : Received: 19 June 2017 / Approved: 20 June 2017 / Online: 20 June 2017 (09:29:11 CEST)
Version 2 : Received: 26 March 2018 / Approved: 27 March 2018 / Online: 27 March 2018 (05:34:38 CEST)

A peer-reviewed article of this Preprint also exists.

Hilpert, S.; Kaldemeyer, C.; Krien, U.; Günther, S.; Wingenbach, C.; Plessmann, G. The Open Energy Modelling Framework (oemof) - A new approach to facilitate open science in energy system modelling. Energy Strategy Reviews 2018, 22, 16-25. Hilpert, S.; Kaldemeyer, C.; Krien, U.; Günther, S.; Wingenbach, C.; Plessmann, G. The Open Energy Modelling Framework (oemof) - A new approach to facilitate open science in energy system modelling. Energy Strategy Reviews 2018, 22, 16-25.

Abstract

Energy system models have become indispensable to shape future energy systems by providing insights into different trajectories. However, sustainable systems with high shares of renewable energy are characterised by growing crosssectoral interdependencies and decentralised structures. To capture important properties of increasingly complex energy systems, sophisticated and flexible modelling environments are needed. This paper presents the Open Energy Modelling Framework (oemof) as a novel approach in energy system modelling, representation and analysis. The framework forms a structured set of tools and sub-frameworks to construct comprehensive energy system models and has been published open source under a free licence. Using a collaborative development approach and extensive documentation on different levels, the framework seeks for a maximum level of transparency. Based on a generic graph based description of energy systems it is well suited to flexibly model complex crosssectoral systems ranging from a distributed or urban to a transnational scale. This makes the framework a multi-purpose modelling environment for strategic planning of future energy systems.

Supplementary and Associated Material

https://github.com/oemof/oemof: oemof source code GitHub

Keywords

decision support; energy system modelling; optimization

Subject

Engineering, Energy and Fuel Technology

Copyright: This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

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