27 Resilient Energy System Design of Low Emission Districts – A Model Chain from National Scenarios to Plant Operation was published in Innovations and challenges of the energy transition in smart city districts on page 415.

District heating systems have a great potential for supporting the energy transition towards a renewa-ble energy system, and could also be an option in less dense populated urban districts and rural communities with a medium heat density. In these cases, distributed thermal energy storages at each building could improve the overall system performance by enabling a leaner sizing of the piping sys-tems due to peak-shaving and reducing the heat losses of the distribution grid. But how can distribut-ed storages already be considered within the design of the district heating network itself? And what are the quantitative benefits with respect to the district heating piping system? This paper answers these questions and presents an open-source optimisation approach for designing the piping network of a district heating system. This includes the optimisation of the network topology, the dimensioning of the pipes, and the consideration of distributed storage options. A linear mixed-integer program-ming model with a high spatial resolution including heat storages at each customer has been imple-mented. Within the QUARREE100 project, the approach is demonstrated on a real world case of an existing district with 129 houses in the provincial town Heide in Northern Germany. In the scenario with 1 m³ heat storages, the thermal losses of the district heating network can be reduced by 10.2 % and the total costs by 13.1 %.

Energy system modelling is of high importance to investigate different scenarios in their technical, economical and environmental feasibility. The interplay of different technologies and energy flows in respective models can be represented as directed graphs in a generic but comprehensible formalism. However, additional effort is needed to create specific models and to derive an optimal sizing or operation of components. To tackle this problem, oemof.solph facilitates the formulation of (mixed-integer) linear programs from a generic object-oriented structure. Its structure allows to create models on different levels of detail by means of predefined components and an optional formulation of additional expressions and constraints. With its open and documented code base, extensive collection of examples and an active community it is useful across many levels, from simple applications to advanced modelling.

The 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. 1 Preprints (www.preprints.org) | NOT PEER-REVIEWED | Posted: 15 February 2017 doi:10.20944/preprints201702.0055.v1

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.

The 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.