The principles of Findability, Accessibility, Interoperability, and Reusability (FAIR) have been put forward to guide optimal sharing of data. The potential for industrial and social innovation is vast. Domain-specific metadata standards are crucial in this context, but are widely missing in the energy sector. This report provides a collaborative response from the low carbon energy research community for addressing the necessity of advancing FAIR metadata standards. We review and test existing metadata practices in the domain based on a series of community workshops. We reflect the perspectives of energy data stakeholders. The outcome is reported in terms of challenges and elicits recommendations for advancing FAIR metadata standards in the energy domain across a broad spectrum of stakeholders.

Energy modelling is the process of using mathematical models to develop abstractions and then seek insights into future energy systems. It can be an abstract academic activity. Or, it can insert threads that influence our development. We argue therefore, that energy modelling that provides policy support (EMoPS) should not only be grounded in rigorous analytics, but also in good governance principles. As, together with other policy actions, it should be accountable. Almost all aspects of society and much of its impact on the environment are influenced by our use of energy. In this context, EMoPS can inspire, motivate, calibrate, and ‘post assess’ energy policy. But, such modeling is often undertaken by too few analysts under time and resource pressure. Building on the advances of ‘class leaders’, we propose that EMoPS should reach for practical goals — including engagement and accountability with the communities it involves, and those it will later affect. (We use the term Ubuntu, meaning ‘I am because you are’ to capture this interdependency). We argue that Ubuntu, together with retrievability, repeatability, reconstructability, interoperability and auditability (U4RIA) of EMoPS should be used to signal the beginnings of a new default practice. We demonstrate how the U4RIA principles can contribute in practice using recent modelling of aspirational energy futures by Costa Rica as a case study. This modelling effort includes community involvement and interfaces and integrates stakeholder involvement. It leaves a trail that allows for its auditing and accountability, while building capacity and sustainable institutional memory.

A mid-2017 survey shows that 28 energy system modeling projects have made public their source code, up from six in 2010, and none in 2000. Another six web-based energy sector database projects and nine hybrid projects were established during this same period, some explicitly to service open modeling. Three distinct yet overlapping drivers can explain this shift in paradigm towards open methods: a desire for improved public transparency, the need for genuine scientific reproducibility, and a nascent experiment to see whether open source development methods can improve academic productivity and quality and perhaps also public trust. The associated source code, datasets, and documentation need suitable open licenses to enable their use, modification, and republication. The choice for software is polarized: teams need only consider maximally permissive (ISC, MIT) or strongly protective (GPLv3) licenses. Selection is influenced by whether code adoption or freedom from capture is uppermost and by the implementation language, distribution architecture, and use of third-party components. Permissive data licenses (CC BY 4.0) are generally favored for datasets to facilitate their recombination and reuse. Official and semi-official energy sector data providers should also prefer permissive licensing for copyrightable material. (C) 2018 The Author. Published by Elsevier Ltd.

In the last decades, energy modelling has supported energy planning by offering insights into the dynamics between energy access, resource use, and sustainable development. Especially in recent years, there has been an attempt to strengthen the science-policy interface and increase the involvement of society in energy planning processes. This has, both in the EU and worldwide, led to the development of open-source and transparent energy modelling practices. This paper describes the role of an open-source energy modelling tool in the energy planning process and highlights its importance for society. Specifically, it describes the existence and characteristics of the relationship between developing an open-source, freely available tool and its application, dissemination and use for policy making. Using the example of the Open Source energy Modelling System (OSeMOSYS), this work focuses on practices that were established within the community and that made the framework's development and application both relevant and scientifically grounded. (C) 2018 Elsevier Ltd. All rights reserved.

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.

Real time algorithm based on time series data abstraction and hybrid bond graph model for diagnosis of switched system