Bridging the resolution gap to improve the assessment of long-term energy transitions

Global energy-economic models, such as MESSAGE with which I work at IIASA, have proven valuable for assessing long-term energy transitions and their environmental implications under a range of policy and technology scenarios. However, the broad geographic and temporal scope of these models has required a trade-off in terms of spatial and temporal resolution with most models employing 5-10 year temporal intervals and large, often continental-scale, regions. This coarse resolution poses a challenge for exploring how fine resolution phenomena, such as water resource constraints and renewable energy intermittency, may influence energy transitions. Thus, there is a need for new approaches and next-generation models that enable the exploration of fine resolution phenomena within the context of global change research. Building upon my expertise in both spatially-explicit and global energy systems modeling, my research seeks to bridge this “resolution gap” in an effort to facilitate novel interdisciplinary research on energy transitions. As examples, two recent research projects are presented that highlight novel approaches for incorporating fine resolution phenomena into the assessment of energy transitions. These projects include the developments of (1) a reduced-form approach to account for the electricity system integration impacts associated with wind and solar intermittency in a global energy-economic model and (2) geospatial supply curves for biofuels with carbon capture and storage (CCS) using spatially-explicit modeling. Finally, I touch upon my latest research, which entails the development of a next-generation energy-economic model for the purpose of enabling linkages among global change models and thus facilitating joint research to better understand how (1) land-energy-water (LEW) interactions, (2) climate change impacts, and (3) heterogeneity in human development and energy resources influence long-term energy transitions.

Speaker: Nils Johnson, International Institute for Applied Systems Analysis