In a significant move to revolutionize America’s energy infrastructure, the U.S. Department of Energy (DOE) has allocated $34 million towards the development of innovative tools designed to facilitate a more robust and reliable electricity grid predominantly powered by wind and solar energy. In conjunction with this investment, the DOE has introduced an additional $10 million funding opportunity aimed at optimizing the interconnection of clean energy sources to the national grid. These concurrent efforts serve to expedite the connection of renewable energy projects and fortify the grid against extreme weather-induced outages. The overarching target of this initiative is aligned with President Biden’s ambitious plan for a 100% clean electricity grid by 2035.
Enhancing Grid Management for a Renewable Future
Renewables such as wind and solar now supply over 20% of the United States’ electricity needs—a percentage that must rise briskly to meet the nation’s climate objectives. The shift towards increasing clean energy uptake brings with it the challenge of managing the variability inherent in these sources. Factors such as climate change-induced temperature rises, the decommissioning of aging power plants, and the surge in electricity demand owing to widespread electrification are all putting strain on the existing grid infrastructure, potentially leading to blackouts if not properly managed.
To tackle this, the DOE’s Solar Energy Technologies Office has selected eleven projects under the Operation and Planning Tools for Inverter-Based Resource Management and Availability for the Future Power System (OPTIMA) program. These ventures seek to devise advanced solutions that optimize the integration and manageability of renewable and storage technologies, thereby enhancing the grid’s adaptability and resilience to dynamic conditions like varying weather and energy demands.
The proud beneficiaries of the OPTIMA program, listed with their designated funding amounts, are:
- Florida International University (Miami, FL) – $2.4 million
- Washington State University (Pullman, WA) – $2.4 million
- Georgia Institute of Technology (Atlanta, GA) – $2.8 million
- Iowa State University (Ames, IA) – $3 million
- Midcontinent Independent System Operator (Carmel, IN) – $3 million
- National Renewable Energy Laboratory (Golden, CO) – Two projects totaling $6.5 million
- University of Connecticut (Storrs, CT) – $3.3 million
- Arizona State University (Tempe, AZ) – $3 million
- Pacific Northwest National Laboratory (Richland, WA) – $3.6 million
- Quanta Technology (Raleigh, NC) – $3.8 million
Confronting the Challenge of Interconnecting Clean Energy
The surge in clean energy has accumulated more than 2,000 gigawatts worth of solar, wind, and storage capacity awaiting transmission interconnections at the close of 2022. The staggering volume of interconnection requests is outstripping the capacity of existing processing frameworks. To streamline this process, the DOE’s Solar Energy Technologies Office and Wind Energy Technologies Office has unveiled the Solar and Wind Interconnection for Future Transmission (SWIFTR) funding project, committing $10 million to refining software tools. These tools are expected to bolster the efficiency of interconnection studies and provide project developers with essential transmission system data, thereby shortening the grid connection lead time for up-and-coming renewable energy projects.
This initiative operates under the broader ambit of the DOE’s Interconnection Innovation e-Xchange (i2X). Launched in 2022 and backed by the President’s Bipartisan Infrastructure Law, i2X seeks to simplify and expedite the interconnection of clean energy and storage technologies. It prioritizes not only the swifter expansion of national grid capacity but also the preservation of grid reliability, resilience, and security. The SWIFTR funding opportunity coincides with i2X’s draft roadmap which delineates robust actions for transmission providers to fast-track the interconnection process, ensuring reliability and creating a more transparent data ecosystem.
