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We are especially grateful to Walter Short who first envisioned and developed the WinDS and ReEDS models. We also thank the NREL analysts who provided input on the technology costs, assumptions, and methodologies in ReEDS, including

AcknowledgmentsWe gratefully acknowledge the many people whose efforts contributed to this report. The ReEDS modeling and analysis team at the National Renewable Energy Laboratory (NREL) was active in developing and testing the ReEDS model v.2018. We also acknowledge the vast number of current and past NREL employees on and beyond the ReEDS team who have participated in data and model development, testing, and analysis. We are especially grateful to Walter Short who first envisioned and developed the Wind Deployment System (WinDS) and ReEDS models. We thank for their comments and improvements on successive versions of this report. Finally, we are grateful to all those who helped sponsor ReEDS model development and analysis, particularly supporters from the U.S. Department of Energy (DOE) but also others who have funded our work over the years.

NREL prints on paper that contains recycled content.1 The post-2030 PV costs continue to decline such that 2050 PV costs are 33% lower than the 2030 targets. See Appendix D for details on pathways that can achieve these low costs. 2 The ATB contains current and future cost and performance projections for the U.S. electricity sector technologies (NREL 2016). The mid-case projections from the ATB are used in these scenarios for all non-PV technologies unless otherwise stated. These mid-case projections include anticipated cost declines for all technologies.

We estimate the technical potential of rooftop solar photovoltaics (PV) for select US cities by combining light detection and ranging (lidar) data, a validated analytical method for determining rooftop PV suitability employing geographic information systems, and modeling of PV electricity generation. We find that rooftop PV's ability to meet estimated city electricity consumption varies widely-from meeting 16% of annual consumption (in Washington, DC) to meeting 88% (in Mission Viejo, CA). Important drivers include average rooftop suitability, household footprint/ per-capita roof space, the quality of the solar resource, and the city's estimated electricity consumption. In addition to city-wide results, we also estimate the ability of aggregations of households to offset their electricity consumption with PV. In a companion article, we will use statistical modeling to extend our results and estimate national rooftop PV technical potential. In addition, our publically available data and methods may help policy makers, utilities, researchers, and others perform customized analyses to meet their specific needs.