Robust Risk Assessment for Park-Level Integrated Energy Systems: A Framework for Adaptive Governance under Deep Uncertainty

Park-level integrated energy systems (PIESs) are critical for achieving climate goals, but their assessment is hampered by deep uncertainty in future technologies and policies. Conventional methods, which seek a single optimal solution, often lead to risky, inflexible commitments. This paper presents a novel three-stage assessment framework designed for adaptive governance under such uncertainty. The framework first enhances credibility by combining literature-based evidence, systematically mined via a knowledge graph, with structured expert judgments. It then improves robustness by replacing simple rankings with a strategic three-way classification: “accept,” “defer,” or “reject.” A case study of four PIES configurations demonstrates the framework’s practical value. It decisively identifies a hybrid-storage system for acceptance and rejects a conventional system. More importantly, it classifies two other viable options into the “defer” category, providing a clear, evidence-based rationale for postponing major investments pending targeted analysis. This work provides a transferable framework that moves beyond optimization to support more adaptive and accountable decision-making for critical energy infrastructure.