The Capacity Expansion Regional Feasibility (CERF) model downscales U.S. state or regional-scale electricity system capacity expansion plans, such as those produced by the Global Change Analysis Model (GCAM-USA), and identifies feasible, site-specific locations for individual new power plants (renewable and non-renewable). CERF combines high-resolution geospatial suitability analyses with an economic algorithm that selects individual plant siting locations based on grid interconnection costs and the locational marginal value of new generation. The model incorporates a wide range of dynamic constraints and opportunities, such as protected lands, population density, existing infrastructure, and water availability. CERF’s downscaling provides a form of “ground-truthing” to 1) ensure that coarser scale expansion planning models are producing feasible futures, 2) illustrate how the power plant landscape evolves over time under different climate, socioeconomic, technology, and policy futures, and 3) help inform regional- and local-scale transmission and generation planning.

CERF is an open-source Python package that operates at a 1 km2 geospatial resolution. Though CERF is currently configured to operate over the United States, it can be easily extended to function for any country or region given the appropriate data prerequisites. CERF uses geospatially referenced suitability criteria developed from a range of sources, including state and federal siting regulations and publicly available documents describing siting constraints faced by recently built power plants. The model includes constraints identified as common to all new power plants, such as avoiding protected lands and critical habitat areas, as well as technology-specific constraints representing particular siting needs, such as minimum mean annual streamflow requirements for thermoelectric cooling water, solar irradiance, and wind speeds. CERF combines the common and technology-specific constraints to determine the 1 km2 grid cells that are suitable for each technology type. The economic algorithm then determines individual power plant siting locations by inducing a competition between technologies in suitable grid cells. This competition is based on the technology-specific costs of connecting to the nearest substation and gas pipeline (if needed) as well as the technology-specific value of new generation in that location (based on locational marginal prices and technology-specific variable operating costs). This algorithm is representative of regional transmission planning and independent power producer decision making practices.