Opening the black box of energy modelling: Strategies and lessons learned (1707.08164v2)

Abstract: 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.

Opening the Black Box of Energy Modelling: Insights on Moving Towards Transparency and Openness

The paper "Opening the black box of energy modelling: Strategies and lessons learned" provides a comprehensive examination of the complexities and strategic decision-making involved in promoting transparency and openness within energy modelling. Using insights from the Open Energy Modelling Initiative (Openmod), the paper highlights the importance of open models and data in transitioning global energy systems amidst regulatory shifts and the need for greenhouse gas reductions. The authors offer a practical guide for researchers on opening model codes and data, addressing intellectual property, licensing, and community building while also highlighting the broader institutional changes necessary for enhanced transparency.

Transparency in Energy Modelling

Historically, energy system planning has been characterized by closed and proprietary approaches, primarily held by research institutions, government agencies, and utilities. However, the evolving landscape, driven by markets' liberalization and the integration of renewable technologies like wind and photovoltaic systems, necessitates open models to facilitate comprehensive and inclusive energy planning. Open energy models promote scientific quality through increased transparency, reproducibility, and collaboration across academic and policy domains. These models enable better regulatory transparency and potentially reduce public opposition to new policies or infrastructure by clarifying decision-making processes.

Practical Considerations for Openness

The paper explores several crucial considerations for researchers aiming to transition to open-source energy modelling:

1. Intellectual Property and Licensing: Establishing intellectual property ownership is critical, with licenses serving as a legal framework for publishing code or data. The choice between permissive and copyleft licenses impacts usage and distribution, and researchers must consider compatibility and institutional requirements.
2. Data Management: Data serves as both input and output in models. Navigating its legal usage, particularly with non-disclosure agreements and absent licenses, is complex. Transparent documentation of data processing is essential to ensure reproducibility and understanding of results and implications.
3. Model Implementation and Tools: The programming languages and tools used in model construction can limit functionalities and openness. Open-source languages and platforms provide broad accessibility, though commercial tools might offer superior performance or usability.
4. Community Building: Beyond access to code and data, successful open projects cultivate active communities through documentation, support structures, tutorials, and collaborative platforms like GitHub. These efforts amplify user and contributor engagement, enhancing model development and application.

Real-World Applications and Constraints

The paper provides illustrative examples such as the development of open-source projects from the outset versus opening existing models. Projects like OSeMOSYS and oemof exemplify how dedicated community-building efforts and inter-institutional collaboration can foster thriving open-source environments. Yet, challenges remain, such as overcoming ingrained institutional practices, proprietary data complexities, and clarity in licensing agreements.

Implications and Future Directions

The adoption of open energy models represents a shift towards more democratic and participatory energy system planning. However, the authors stress the importance of institutional reforms to support openness. This includes encouraging open licenses by statistical and governmental data providers, modifying research funding conditions to favor open models, and recognizing software and data contributions in academic assessments.

In conclusion, the trajectory of energy modelling is clear: moving towards openness is not only desirable but imperative for coping with contemporary challenges in energy system planning. This paper provides detailed, practical guidance to facilitate this transition, ensuring that energy models serve as transparent and collaborative tools in the quest for sustainable energy solutions. Future research and implementation in the field should focus on addressing institutional inertia and enhancing cross-disciplinary collaborations to achieve these goals.