Integrating society within energy systems modelling, thereby capturing societal preferences and iterative actions within energy modelling frameworks was one of the key challenges discussed at the Energy Modelling Insights for Iterative Decision-Making conference hosted by the University of Cambridge earlier this year.

The 3rd Annual Conference of the wholeSEM consortium (Whole Systems Energy Modelling) was attended by over 100 leading energy modellers from all over the world, who took part in a series of discussion sessions with government and industrial model users and consumers of model outputs, to discuss how to better link and iterate model insights into real world decision-making.

Other main themes at the conference included broadening the scope of energy modelling to include wider geographical drivers, to link to other technical, economic and physical systems, and to introduce new disciplinary viewpoints. The participants also discussed strategic vs. incremental investment under policy uncertainty - assessing the trade-offs between long-term high upfront cost and possibly irreversible investments, with short term priorities and constraints.

According to the conference report, key insights emerging from the discussions at the conference included:

• The advantages of considering wider impacts (e.g., on air pollution, social indicators, employment) and iterating these metrics – that are key for decision-makers – back into the modelling process;
• A clear focus on uncertainty in model inputs and outputs, even if the uncertainty ranges can be very large;
• The usefulness of exploratory modelling to understand possible tipping points, feedbacks and new futures;
• A continuous consideration of model engagement, information, interpretation and influence;
• The avoidance of modelling silos – interdisciplinarity is difficult to accomplish, but can enable the insights that decision-makers need;
• The recognition that decision-makers often exist in a silo (e.g., a government department, a sector of industry) and a broader set of interdisciplinary model insights is key for broadening their viewpoint.