Exploring Robust Early-Stage Decisions in Energy Transitions Using Near-Optimal Pathways and Multi-Armed Bandits

Kchaou, Mahdi;Coppitters, Diederik;Contino, Francesco
(2026) ESCAPE36 (21.June.2026)

Files

LAPSE-2026.0274-1v1.pdf
  • Open Access
  • Adobe PDF
  • 798.99 KB

Details

Authors
  • Kchaou, MahdiInstitute of Mechanics, Materials and Civil Engineering (iMMC), Université catholique de Louvain (UCLouvain), Louvain-la-Neuve, Belgium
    Author
  • Coppitters, DiederikInstitute of Mechanics, Materials and Civil Engineering (iMMC), Université catholique de Louvain (UCLouvain), Louvain-la-Neuve, Belgium
    Author
  • Contino, FrancescoInstitute of Mechanics, Materials and Civil Engineering (iMMC), Université catholique de Louvain (UCLouvain), Louvain-la-Neuve, Belgium
    Author
Abstract
(en) Although rare, unexpected events such as financial crises, geopolitical conflicts, and pandemics have reshaped reality in recent years. Despite their strong potential to affect the energy transition, such events are still largely overlooked in energy planning studies. Ignoring them can lead to poorly informed decisions that may jeopardize the transition. Identifying early-stage decisions that remain robust under unexpected events is therefore essential. To address this challenge, EnergyScope Pathway, a whole-energy system model with limited foresight, is applied to Belgium. To increase the likelihood of a successful transition, the Modeling to Generate Alternatives approach is used to diversify early-stage decisions in 2035. These alternatives are allowed to be up to 10% more expensive than the cost-optimal solution. However, the large number of alternative designs is difficult to navigate for decision makers. To address this, a decision-support framework based on the Multi-Armed Bandit framework is used to identify early-stage decisions that are most robust to future unexpected events. In this step, the remaining transition phases are optimized under unexpected events sampled within predefined impact ranges. The results show that, under normal conditions, there is a high degree of flexibility in the decision space for the 2030–2035 phase, with many technologies or resources that can be entirely omitted. However, robust early-stage decisions rely on a diverse energy generation portfolio, with a stronger emphasis on wind deployment, early mobility shifts toward battery electric vehicles, and the import of e-fuels. These insights can help decision makers steer the energy transition toward a robust path from the beginning. While Belgium is used as a case study, this framework is transferable to other contexts.
Affiliations

Citations

Kchaou, M., Coppitters, D., & Contino, F. (2026). Exploring Robust Early-Stage Decisions in Energy Transitions Using Near-Optimal Pathways and Multi-Armed Bandits. Systems and Control Transactions, 5, 574-582. https://doi.org/10.69997/sct.169454 (Original work published 2026)