PNNL

Abstract

Multi-sector human-Earth system models and electric sector only models are both extensively used to provide guidance on long-term electricity capacity expansion. While both classes of models have strengths, they are limited in their ability to provide robust decision support by not simultaneously including sectoral, spatial, temporal, and process detail under one consistent framework. We integrate two state-of-the-art models (GCAM-USA, a multi-sector human-Earth system model, and ReEDS, an electric sector only model) with starkly different architectures to provide a robust baseline for projections of U.S. electricity capacity expansion. We develop processes to harmonize assumptions around key drivers of electricity capacity expansion. We harmonize individual and combinations of those drivers to examine the sensitivity of model solution harmonization to changes in assumptions surrounding the drivers. Our results suggest that solution harmonization is most sensitive to assumptions about fuel prices and renewable resource characteristics. In addition, despite best efforts, irreconcilable structural differences in the representations of key drivers (e.g. electricity trade) lead to variations in the degree of solution harmonization across space, time, and technology. More broadly, our results highlight the tradeoffs in harmonization of drivers in facilitating solution harmonization of models with fundamentally different structures but nested scope.