The global energy system is undergoing a major transition, and in energy planning and decision-making across governments, industry and academia, models play a crucial role. Because of their policy relevance and contested nature, the transparency and open availability of energy models and data are of particular importance. Here we provide a practical how-to guide based on the collective experience of members of the Open Energy Modelling Initiative (Openmod). We discuss key steps to consider when opening code and data, including determining intellectual property ownership, choosing a licence and appropriate modelling languages, distributing code and data, and providing support and building communities. After illustrating these decisions with examples and lessons learned from the community, we conclude that even though individual researchers' choices are important, institutional changes are still also necessary for more openness and transparency in energy research

Energy system models have become indispensable tools for planning future energy systems by providing insights into different development 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 is becoming increasingly important in energy system modelling. This paper presents the Open Energy Modelling Framework (oemof) as a novel approach to energy system modelling, representation and analysis. The framework provides a toolbox to construct comprehensive energy system models and has been published open source under a free licence. Through collaborative development based on open processes, the framework supports a maximum level of participation, transparency and 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 at scales ranging from urban to transnational.

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.

Background: The research field of energy system analysis is faced with the challenge of increasingly complex systems and their sustainable transition. The challenges are not only on a technical level but also connected to societal aspects. Energy system modelling plays a decisive role in this field, and model properties define how useful it is in regard to the existing challenges. For energy system models, evaluation methods exist, but we argue that many decisions upon properties are rather made on the model generator or framework level. Thus, this paper presents a qualitative approach to evaluate frameworks in a transparent and structured way regarding their suitability to tackle energy system modelling challenges. Methods: Current main challenges and framework properties that potentially contribute to tackle these challenges are derived from a literature review. The resulting contribution matrix and the described application procedure is then applied exemplarily in a case study in which the properties of the Open Energy Modelling Framework are checked for suitability to each challenge. Results: We identified complexity (1), scientific standards (2), utilisation (3), interdisciplinary modelling (4), and uncertainty (5) as the main challenges. We suggest three major property categories of frameworks with regard to their capability to tackle the challenges: open-source philosophy (1), collaborative modelling (2), and structural properties (3). General findings of the detailed mapping of challenges and properties are that an open-source approach is a precondition for complying with scientific standards and that approaches to tackle the challenges complexity and uncertainty counteract each other. More research in the field of complexity reduction within energy system models is needed. Furthermore, while framework properties can support to address problems of result communication and interdisciplinary modelling, an important part can only be addressed by communication and organisational structures, thus, on a behavioural and social level. Conclusions: We conclude that the relevance of energy system analysis tools needs to be reviewed critically. Their suitability for tackling the identified challenges deserves to be emphasised. The approach presented here is one contribution to improve current evaluation methods by adding this aspect.

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Several studies show that heat pumps need to play a major role for space heating and hot water supply in highly decarbonised energy systems. The degree of elasticity of this additional electricity demand can have a significant impact on the electricity system. This paper investigates the effect of decentral heat pump flexibilisation through thermal energy storage units on electricity storage investment. The analysis is carried using an open source model for the German electricity system based on the Open Energy Modelling Framework (oemof). Results highlight the importance of flexible heat pump operation in 100% renewable energy systems and relate well to findings of other existing studies. Flexibilisation of heat pumps in the German energy system can reduce the need for electricity storage units significantly. While no impact was found for systems with a share below 80% renewable energy, investment in short term storage units is reduced by up to 42–62% in systems with shares of more than 80% renewable energy. In contrast, the impact on long term electricity storage investment was comparatively low in all modelled scenarios. Conducted sensitivity analyses show that both findings are rather insensitive with regard to the available biomass for electricity supply as well as to changes in the heat demand covered by heat pumps. Economically flexible heat pump operation has only a minor effect on system costs. However, the indirect replacement of battery with thermal energy storage units is environmentally beneficial due a lower resource consumption of minerals.

These authors contributed equally to this work. AbstractThe process of modelling energy systems is accompanied by challenges inherently connected with mathematical modelling. However, due to modern realities in the 21st century, existing challenges are gaining in magnitude and are supplemented with new ones. Modellers are confronted with a rising complexity of energy systems and high uncertainties on different levels. In addition, interdisciplinary modelling is necessary for getting insight in mechanisms of an integrated world. At the same time models need to meet scientific standards as public acceptance becomes increasingly important. In this intricate environment model application as well as result communication and interpretation is also getting more difficult.In this paper we present the open energy modelling framework (oemof) as a novel approach for energy system modelling and derive its contribution to existing challenges. Therefore, based on literature review, we outline challenges for energy system modelling as well as existing and emerging approaches. Based on a description of the philosophy and elementary structural elements of oemof, a qualitative analysis of the framework with regard to the challenges is undertaken. Inherent features of oemof such as the open source, open data, non-proprietary and collaborative modelling approach are preconditions to meet modern realities of energy modelling. Additionally, a generic basis with an object-oriented implementation allows to tackle challenges related to complexity of highly integrated future energy systems and sets the foundation to address uncertainty in the future. Experiences from the collaborative modelling approach can enrich interdisciplinary modelling activities.Our analysis concludes that there are remaining challenges that can neither be tackled by a model nor a modelling framework. Among these are problems connected to result communication and interpretation.

The transformation of heat supply structures towards 4th generation district heating (4GDH) involves lower supply temperatures and a shift in technology. In order to assess the economic viability of the respective systems, adequate unit commitment models are needed. However, maintaining the formal requirements, while reducing the computational efforts of these models, often includes simplifications such as the assumption of constant supply temperatures. This study investigates the effect of introducing varying supply temperatures in mixed-integer linear programming models. Based on a case study of a municipal district heating system, how the temperature integration approach affects unit commitment and technology assessment for different temperature levels and scenarios is analyzed. In particular, three supply temperature levels are investigated with both variable and constant temperatures in two scenarios. Results indicate that lower flow temperature levels in the heating network tend to favor internal combustion engines, combined cycle power plants, and heat pumps; while back pressure steam turbines, peak loads, and electric boilers show declining operating hours. Furthermore, the effect of varying versus constant temperatures at the same temperature level is rather small, at least as long as technical restrictions do not come into play. Finally, it is found that the effect of changing temperature on a technology assessment is comparably small as opposed to adaptions in the regulatory framework.