Scenario discovery with an integrated assessment model to identify robust, policy-relevant scenarios for capacity expansion in Latin America

Abstract

The ongoing global transition to a deeply decarbonized electricity system represents a complex problem. Deep uncertainty in the future pathways of power system capacity expansion and interactions across sectors has led stakeholders to seek out robust methods capable of informing multi-scale, multi-sector tradeoffs among policy pathways within the energy-water-food nexus. In this study, scenario discovery is applied to a large scenario ensemble generated using a global-scale integrated assessment model with a regional focus on Latin America. Scenario discovery is a powerful method for identifying robust, policy-relevant scenarios from large, many-dimensional ensembles of model realizations. Here, ten uncertain sensitivity factors consistent with previous analyses are varied within the model configuration, representing technological costs and efficiencies, advanced electrification, institutional factors, and national climate pledges, among others. The resulting scenario ensemble maps out the impacts of a combinatorial time-evolving uncertainty space defined by these sensitivity factors, using generation mix, electricity cost, energy burden, and energy intensity as power system performance metrics. Additional metrics are utilized to explore cross-sectoral implications of scenarios. The scenario discovery analysis identifies the key global drivers of regional outcomes in Latin America, as well as tradeoffs and synergies regarding climate change mitigation and the future evolution of the Latin American electric power system. Our results underscore the importance of considering coupled systems and the advantages of large-scale scenario ensembles in capacity expansion analyses.