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Creating Agent-Based Energy Transition Management Models That Can Uncover Profitable Pathways to Climate Change Mitigation

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  • Auke Hoekstra
  • Maarten Steinbuch
  • Geert Verbong

Abstract

The energy domain is still dominated by equilibrium models that underestimate both the dangers and opportunities related to climate change. In reality, climate and energy systems contain tipping points, feedback loops, and exponential developments. This paper describes how to create realistic energy transition management models: quantitative models that can discover profitable pathways from fossil fuels to renewable energy. We review the literature regarding agent-based economics, disruptive innovation, and transition management and determine the following requirements. Actors must be detailed, heterogeneous, interacting, learning, and strategizing. Technology should be represented as a detailed and heterogeneous portfolio that can develop in a bottom-up manner, using endogenous feedback loops. Assumptions about discount rates and the social cost of carbon should be configurable. The model should contain interactions between the global, national, local, and individual level. A review of modelling techniques shows that equilibrium models are unsuitable and that system dynamics and discrete event simulation are too limited. The agent-based approach is found to be uniquely suited for the complex adaptive sociotechnical systems that must be modelled. But the choice for agent-based models does not mean a rejection of other approaches because they can be accommodated within the agent-based framework. We conclude with practical guidelines.

Suggested Citation

  • Auke Hoekstra & Maarten Steinbuch & Geert Verbong, 2017. "Creating Agent-Based Energy Transition Management Models That Can Uncover Profitable Pathways to Climate Change Mitigation," Complexity, Hindawi, vol. 2017, pages 1-23, December.
    • Handle: RePEc:hin:complx:1967645
    DOI: 10.1155/2017/1967645
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    5. López Prol, Javier & Zilberman, David, 2023. "No alarms and no surprises: Dynamics of renewable energy curtailment in California," Energy Economics, Elsevier, vol. 126(C).
    6. Javier L'opez Prol & Wolf-Peter Schill, 2020. "The Economics of Variable Renewables and Electricity Storage," Papers 2012.15371, arXiv.org.
    7. Li, Pei-Hao & Barazza, Elsa & Strachan, Neil, 2022. "The influences of non-optimal investments on the scale-up of smart local energy systems in the UK electricity market," Energy Policy, Elsevier, vol. 170(C).
    8. Bretschger, Lucas, 2024. "Energy transition and climate change abatement: A macroeconomic analysis," Resource and Energy Economics, Elsevier, vol. 76(C).
    9. Barbrook-Johnson, Peter & Tankwa, Brendon, 2023. "Increasing inequality between countries in key renewable energy costs," INET Oxford Working Papers 2023-20, Institute for New Economic Thinking at the Oxford Martin School, University of Oxford.
    10. Barazza, Elsa & Strachan, Neil, 2020. "The impact of heterogeneous market players with bounded-rationality on the electricity sector low-carbon transition," Energy Policy, Elsevier, vol. 138(C).

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