Comparing expert elicitation and model-based probabilistic technology cost forecasts for the energy transition.

ABSTRACT: We conduct a systematic comparison of technology cost forecasts produced by expert elicitation methods and model-based methods. Our focus is on energy technologies due to their importance for energy and climate policy. We assess the performance of several forecasting methods by generating probabilistic technology cost forecasts rooted at various years in the past and then comparing these with observed costs in 2019. We do this for six technologies for which both observed and elicited data are available. The model-based methods use either deployment (Wright's law) or time (Moore's law) to forecast costs. We show that, overall, model-based forecasting methods outperformed elicitation methods. Their 2019 cost forecast ranges contained the observed values much more often than elicitations, and

SUBMITTER: Meng J 

PROVIDER: S-EPMC8271727 | biostudies-literature | 2021 Jul

REPOSITORIES: biostudies-literature