Researchers have developed a new generation of energy system models representing U.S. electricity generation, transmission, and demand that promises to help decisionmakers understand how different policies will speed or inhibit the decarbonization of the U.S. energy system. Yet these models differ in various respects, and there is a need to gain insight about how these individual energy system models compare to one another. To fully unlock the decision-making usefulness of these powerful next generation energy system models, a nuanced understanding is needed to determine how the evaluations produced by these models vary and what features of the models explain such variance. This grant supports research by a multi-institution team led by Oleg Lugovoy at the Environmental Defense Fund to compare a set of cutting-edge, open-source electricity system planning models across a range of different decarbonization scenarios. Lugovoy’s team will compare four models (known as GenX, Switch, Temoa, and USENSYS) using the PowerGenome platform to conduct their comparisons and analyze the results. The models will be compared across two decarbonization scenarios, a business-as-usual scenario and a high-renewables scenario, all drawing on the same input data. Grant funds will allow the team to produce 4-6 publications, train 2 postdoctoral researchers in energy system modeling intercomparison, produce a GitHub data repository, and disseminate model comparison results to practitioner stakeholders. Finally, the team will convene 2-4 public workshops to train those interested in learning how to use the open-source models and the results of the model intercomparison project.