@article{decarolis_babaee_li_kanungo_2016, title={Modelling to generate alternatives with an energy system optimization model}, volume={79}, ISSN={["1873-6726"]}, DOI={10.1016/j.envsoft.2015.11.019}, abstractNote={Energy system optimization models (ESOMs) should be used in an interactive way to uncover knife-edge solutions, explore alternative system configurations, and suggest different ways to achieve policy objectives under conditions of deep uncertainty. In this paper, we do so by employing an existing optimization technique called modeling to generate alternatives (MGA), which involves a change in the model structure in order to systematically explore the near-optimal decision space. The MGA capability is incorporated into Tools for Energy Model Optimization and Analysis (Temoa), an open source framework that also includes a technology rich, bottom up ESOM. In this analysis, Temoa is used to explore alternative energy futures in a simplified single region energy system that represents the U.S. electric sector and a portion of the light duty transport sector. Given the dataset limitations, we place greater emphasis on the methodological approach rather than specific results.}, journal={ENVIRONMENTAL MODELLING & SOFTWARE}, author={DeCarolis, J. F. and Babaee, S. and Li, B. and Kanungo, S.}, year={2016}, month={May}, pages={300–310} }
 @article{babaee_nagpure_decarolis_2014, title={How Much Do Electric Drive Vehicles Matter to Future U.S. Emissions?}, volume={48}, ISSN={["1520-5851"]}, DOI={10.1021/es4045677}, abstractNote={Hybrid, plug-in hybrid, and battery electric vehicles--known collectively as electric drive vehicles (EDVs)--may represent a clean and affordable option to meet growing U.S. light duty vehicle (LDV) demand. The goal of this study is 2-fold: identify the conditions under which EDVs achieve high LDV market penetration in the U.S. and quantify the associated change in CO2, SO2, and NOX emissions through midcentury. We employ the Integrated MARKAL-EFOM System (TIMES), a bottom-up energy system model, along with a U.S. data set developed for this analysis. To characterize EDV deployment through 2050, varying assumptions related to crude oil and natural gas prices, a CO2 policy, a federal renewable portfolio standard, and vehicle battery cost were combined to form 108 different scenarios. Across these scenarios, oil prices and battery cost have the biggest effect on EDV deployment. The model results do not demonstrate a clear and consistent trend toward lower system-wide emissions as EDV deployment increases. In addition to the trade-off between lower tailpipe and higher electric sector emissions associated with plug-in vehicles, the scenarios produce system-wide emissions effects that often mask the effect of EDV deployment.}, number={3}, journal={ENVIRONMENTAL SCIENCE & TECHNOLOGY}, author={Babaee, Samaneh and Nagpure, Ajay S. and DeCarolis, Joseph F.}, year={2014}, month={Feb}, pages={1382–1390} }