Characterizing decision making under deep uncertainty for model-based energy transitions

Sustainable energy transitions (SET) are complex processes spanning over decades and subject to deep uncertainty from a variety of sources, such as climate change, technology development, and social and institutional contexts. Although this is a recognized issue in SET, previous studies and reviews in this field lack a comprehensive identification of the deep uncertainty sources and the capacities of methods to cope with them. Based on the review of nearly 100 selected references that involve 19 case studies, this review systematically identifies and characterizes these sources of deep uncertainty for the first time. In doing so, it considers the techno-economic, political, and socio-technical dimensions of SET and analyses Decision Making under Deep Uncertainty (DMDU) methods to cope with the specific characteristics of SET. The analysis of the applicability of DMDU methodologies to SET reveals that no predominant methodology covers all aspects of deep uncertainty sources and that the DMDU paradigm could benefit from a multi-method perspective specifically designed for SET. Thus, through some final recommendations, this review aims to provide guidance in the process of deep uncertainty characterization in SET studies and to constitute a basis to support decision-makers in selecting the adequate DMDU method or on generating new dedicated approaches for conducting SET studies under deep uncertainty considering the specific local contexts.