Improving consistency among models of overlapping scope in multi-sector studies: The case of electricity capacity expansion scenarios

Highlights: • Long-term quantitative scenarios produced by different models could be inconsistent. • We study consistency of capacity expansion scenarios from 2 very different models. • Harmonization of some input assumptions substantially improves consistency. • Examples of such assumptions are fuel prices, renewable resources, retirements, and demand. -- Abstract: Multi-decadal scenarios produced by modeling studies are used to study the evolution of key infrastructure that cuts across energy, water, and land systems. Scenarios produced by different models contain inconsistencies due to disparate model structures and assumptions. Although inconsistencies can characterize structural uncertainties, they could have important consequences in various contexts such as multi-sector energy-water-land studies that couple multiple models. In such studies, it is important for models with overlapping scope (models having different sectoral, regional, temporal, and process details but producing scenarios for some common output variable(s)) to produce consistent scenarios of common output variable(s) to minimize propagation of inconsistent information. Using the example of baseline electricity capacity expansion scenarios produced by two models with overlapping scope, we explore cross-model scenario consistency (extent to which projections for a common scenario variable(s) diverge). We define a quantitative metric of consistency and examine the sensitivity of consistency of the models' electricity generation by technology outputs to changes in harmonization of assumptions surrounding the representations of key capacity expansion drivers such as fuel prices, renewable resources, demand, and retirements. Our study establishes a framework to systematically examine scenario consistency. In addition, our study utilizes complementary features of well-established models to produce consistent baseline electricity capacity expansion scenarios which can then be used in multi-sector studies.