Improving the energy efficiency of building stock, commercial equipment, and household appliances can have a major positive impact on energy use, carbon emissions, and building services. Sub-national regions such as the U.S. states wish to increase energy efficiency, reduce carbon emissions, or adapt to climate change. Evaluating sub-national policies to reduce energy use and emissions is difficult because of the large uncertainties in socioeconomic factors, technology performance and cost and energy and climate policies. Climate change itself may undercut such policies. However, assessing all of the uncertainties of large-scale energy and climate models by performing thousands of model runs can be a significant modeling effort with its accompanying computational burden. By applying fractional-factorial methods to the GCAM-USA 50-state integrated-assessment model in the context of a particular policy question, this paper demonstrates how a decision-focused sensitivity analysis strategy can greatly reduce computational burden in the presence of uncertainty and reveal the important drivers for decisions and more detailed uncertainty analysis. (C) 2014 Elsevier B.V. All rights reserved.
Scott, MJ; Daly, DS; Zhou, YY; Rice, JS; Patel, PL; McJeon, HC; Kyle, GP; Kim, SH; Eom, JY; Clarke, LE
Evaluating sub-national building-energy efficiency policy options under uncertainty: Efficient sensitivity testing of alternative climate, technological, and socioeconomic futures in a regional integrated-assessment model
Energy Economics