Decision-making under deep uncertainty: A methodology for the future-proof design of energy systems

The transition of energy systems is essential for industrial and societal decarbonization. However, decision-makers face deep uncertainty regarding future technology costs, energy-mix developments, and political conditions. Therefore, a methodology for the scenario-based design of energy systems that integrates principles from robust optimization, adaptive planning, and minimax regret to support future-proof design choices is needed. The methodology presented targets decentralized energy systems, such as those of manufacturing companies or urban environments. It explores a wide range of simulation-based scenarios, applies a performance-corridor heuristic to cluster them, and identifies a robust design per cluster. These clusters act as design pathways, each paired with a reference guideline that indicate when the implemented system should be adapted. This methodology is applied to a case study of a manufacturing company relocating from Germany to Singapore. Using projections consistent with Singapore’s energy system transition strategies, the methodology condenses different system configurations into various application strategies that satisfy operational reliability. It further enables evaluation of both cost and resilience trade-offs while ensuring compliance with decarbonization targets across all scenarios. By compressing vast scenario spaces into actionable design pathways and contingency points, the methodology provides decision-makers like energy system designer with a transparent framework for embedding net-zero compatibility and resilience into industrial and urban energy system design.