Decision Making under Deep Uncertainty in long-term energy planning: A review and hybrid deliberation-with-analysis workflow

Long-term energy planning is a decision-making challenge under deep uncertainty. This systematic review assesses how Decision Making under Deep Uncertainty (DMDU) approaches are applied in energy planning and proposes a hybrid deliberation-with-analysis workflow to support adaptive, stakeholder-informed decisions. The review covers electricity, buildings, heating, transport, and cross-sector systems. A structured search identified 474 records; 158 full texts were screened, yielding 39 studies (2016–2026). Applications are concentrated in high-income, data-rich, and institutionally mature contexts, with limited use in lower- and middle-income countries. Among DMDU approaches, Exploratory Modelling and Analysis (EMA; 36% of studies) and Robust Decision Making (RDM; 31% of studies) are the most commonly used. Uncertainty treatment is predominantly parametric rather than structural. Although many studies assess robustness and identify vulnerabilities, these insights are rarely translated into adaptive, implementable decisions co-developed with stakeholders. Stakeholder engagement is often limited or absent, even in decision-oriented analyses. In response, this paper proposes a hybrid workflow integrating participatory problem framing, exploratory modelling, vulnerability analysis, and robustness assessment, culminating in the co-development of adaptive strategies. The framework emphasises iterative, cyclical engagement between analysis and deliberation to translate uncertainty insights into practical decision support. It provides a structured pathway for embedding stakeholder input and adaptive design into long-term energy planning under deep uncertainty.