2020 Workshop Summary

September 17 and 18, 2020

We held an invitation-only workshop on Macro-Energy Systems in September 2020 via Zoom. In August 2019, we published a paper in Joule outlining the need for a recognized discipline and academic infrastructure supporting research and researchers focusing on large scale energy systems and the energy transition, a discipline that we named Macro-Energy Systems. This workshop represented the next step towards the realization of the vision we laid out in this paper. Additionally, a recorded seminar discussing Macro-Energy Systems and some thoughts about next steps can be found here.

There were two key objectives of the Macro-Energy Systems workshop:

  1. To bring together the key participants of this community to discuss and identify the boundaries, key unanswered questions, and foundational knowledge of the field encompassed by Macro-Energy Systems

  2. Create ongoing support for the academic infrastructure that can sustain Macro-Energy Systems (MES) as an active community.

Key sessions of the workshop addressed topics such as ‘What are the frontiers of MES research currently?’, ‘What are major critiques of MES work and how have we or might we respond to them?’, and ‘What are the skills students need to learn to be successful in MES?’. The small workshop was held via Zoom meetings with sessions conducted as highly interactive panel discussions.

 

Panel 1: Frontiers of Macro-Energy Systems Research

  • Research directions have moved from technical feasibility and energy transition pathways to understanding other non-economic and non-technical bottlenecks, with a focus on distributional impacts

  • Decision support (for policy makers, investors and non academic users) provided by models is crucial, and maintaining model transparency, open access and replicability are critical for achieving this goal

  • Systems thinking is challenging and we need to be deliberative about analyses boundaries and how models can be expanded or combined meaningfully with other models (“the model of everything”); a ‘theory of models’ will help

  • As we incorporate additional objectives (employment effects, energy poverty, pollution), it becomes important to think about how tradeoffs can be formalized; groups affected the most by these tradeoffs need to have a seat at the modeling table

  • We also need to expand our research focus to include non-electricity and non-developed world centered analyses, and start to understand how to include the demand side in a better way

Panel 2: Critiques of Macro-Energy Systems Research and Our Responses as a Field

  • The anonymized panelist poll identified the most important critiques of MES as (1) economic impacts, (2) policy realism, (3) tail risks, and (4) equity

    • Economic Impacts: direct and physical effects of climate change are often considered, but indirect impacts are often underrepresented and speculative, because they depend more on response strategy

    • Policy Realism: there is a disconnect between policy simplicity used in research and the piecemeal/ heterogeneous policies implemented in reality. The multitude of objectives (emissions, energy security, poverty, equity) of real-world policy makers may also be excluded from more traditional cost-based analyses

    • Tail Risks: these can have significant impacts of modelling outcomes, yet computational, data-sourcing, or other restrictions often limit their presence in MES modeling

    • Equity: this is critical to include in models, and strides have been made since their inclusion in the SDG, though including access to energy remains a gap in many large models currently

Panel 3: Educating Future Macro-Energy Systems Researchers

  • Exercises and real world examples (i.e., learning-by-doing) can help students gain insights

  • Teachers and students will benefit from a shared repository, where teaching materials, exercises and games, models and codes can be shared; cross-institutional approach can help facilitation collaboration in educating researchers

  • More training on open-source collaborative scientific software development and coding can be important in educating macro-energy systems researchers

  • Data-driven ways of teaching dynamics and complexity of macro-energy systems can help provide insights in parallel with traditional optimization approach

  • The modeling and analysis tasks require multiple steps and skills from both classroom and workplace

  • Better instruction on coding practice, problem formulation and fundamental interdisciplinary skills/knowledge, among others, are three main areas for education to improve upon

  • Political science/political economics and non-economic behaviors are the two most neglected topics in educating energy modelers

  • Optimization, economics and uncertainty analysis are among the most important skills that people are glad to be trained on

Panel 4: Academic Infrastructure to Support Macro-Energy Systems

  • Discussed in breakout rooms

  • Website is created to serve as central place for educational resources, research community information and seminar series organization