Wind is a clean, enduring energy resource with the capacity to satisfy 20% or more of U.S. electricity demand. Presently, wind potential is limited by a paucity of electrical transmission lines and/or capacity between promising wind resources and primary load centers. We present the model SimWIND to address this shortfall. SimWIND is an integrated optimization model for the geospatial arrangement and cost minimization of wind‐power generation–transmission–delivery infrastructure. Given a set of possible wind‐farm sites, the model simultaneously determines (1) where and how much power to generate and (2) where to build new transmission infrastructure and with what capacity in order to minimize the cost for delivering a targeted amount of power to load. Costs and routing of transmission lines consider geographic and social constraints as well as electricity losses. We apply our model to the Electric Reliability Council of Texas (ERCOT) Interconnection, considering scenarios that deliver up to 20GW of new wind power. We show that SimWIND could potentially reduce ERCOT's projected ˜$5B transmission network upgrade line length and associated costs by 50%. These results suggest that SimWIND's coupled generation–transmission–delivery modeling approach could play a critical role in enhancing planning efforts and reducing costs for wind energy integration.
