A successful transmission network requires deliberate planning, and a new and different approach. One that identifies long-term, flexible, and interregional solutions that will meet national interests. Modernizing transmission planning can provide greater certainty to drive investment to the highest-need transmission projects and enable development of the projects with the largest long-term benefit for consumers.
National Transmission Planning Study
The National Transmission Planning Study will identify transmission for providing broad-scale benefits to electric customers; inform regional and interregional transmission planning processes; and identify interregional and national strategies to accelerate decarbonization while maintaining system reliability.
Transmission Needs Study
Formally known as the National Electric Transmission Congestion Study, the Transmission Needs Study will identify high-priority national transmission needs and provide information about capacity constraints and congestion on the nation’s electric transmission grid. Where previous Congestion Studies were limited to consider only historic congestion, this study considers both historic and anticipated future transmission needs driven by the increase in renewables, and transportation and building electrification.
Atlantic Offshore Wind Transmission Study
To inform the integration of offshore wind (OSW), DOE will conduct supportive analyses to identify transmission pathways and develop transmission strategies to integrate OSW, consistent with the Administration's goal of 30 gigawatts of OSW by 2030 and to set the stage for a more ambitious 2050 OSW deployment target. In November 2021, DOE launched the Atlantic Offshore Wind Transmission Study, a two-year study led by National Renewable Energy Laboratory (NREL) and Pacific Northwest National Laboratory (PNNL). Through robust engagement with diversified stakeholder groups, this work evaluates coordinated transmission solutions to enable OSW energy deployment along the U.S. Atlantic Coast, addressing gaps in existing analyses.