Abstract

Sustainable Energy Transitions (SET) evolve under different levels of uncertainty, with deep uncertainty being the most severe. While the Decision Making under Deep Uncertainty (DMDU) approach offers methodologies to navigate problems under the highest uncertainty levels, its integration in power systems planning remains limited. Furthermore, DMDU often neglects crucial contexts for policymaking, such as the organizational context, challenging its applicability. Addressing this issue, this paper introduces a novel framework for both selecting the most suitable DMDU method and to integrate it into institutions developing power system expansion planning. This framework is based on thoroughly characterizing the institution's decision-making process and its context and then aligning it with available DMDU methods using a common basis for comparison. Following this approach, a detailed illustrative case study is conducted on the power system expansion planning developed by the Chilean Independent System Operator, with Robust Decision Making (RDM) emerging as the most suitable DMDU method. This application considers developing a new model for co-optimizing investments in transmission, generation, and storage infrastructure, and novel visualizations for trajectories of opportunity and vulnerability regions during Scenario Discovery. Simulating 1000 cases, a robust strategy is identified by quantifying the trade-off between emissions and costs, and the resulting plans are compared to plans without RDM. The resulting generation and storage plans are similar with significant differences in the transmission plan. Finally, this research discusses the proposed framework's benefits, contributing to scenario systematization and agency recognition, as well as enhancing robustness and adaptability of power system plans in the context of SET.