Preprint Article Version 2 This version is not peer-reviewed

The Open Energy Modelling Framework (oemof) - A New Approach to Facilitate Open Science in Energy System Modelling

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.

Journal reference: Energy Strategy Reviews 2018, 22, 16-25
DOI: 10.1016/j.esr.2018.07.001

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 characterized by growing cross-sectoral interdependencies and decentralized structures. To capture important properties of increasingly complex energy systems, sophisticated and flexible modelling tools are needed. At the same time open science becomes increasingly important in energy system modelling. This paper presents the Open Energy Modelling Framework (oemof) as a novel approach in energy system modelling, representation and analysis. The framework forms a toolbox to construct comprehensive energy system models and has been published open source under a free license. With a collaborative development based on open processes the framework seeks for a maximum level of participation and transparency to facilitate open science principles in energy system modelling. Based on a generic graph based description of energy systems it is well suited to flexibly model complex cross-sectoral systems and incorporate various modelling approaches. This makes the framework a multi-purpose modelling environment for modelling and analyzing different systems ranging from an urban to a transnational scale.

Subject Areas

decision support; energy system modelling; optimization; collaborative development; open science

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