The U.S. Department of Energy’s Office of Electricity (OE) is working to develop technical solutions, issue best practices, and strengthen coordination among utilities, national labs, and government agencies to prevent grid-related wildfire ignitions.
The U.S. Department of Energy’s Office of Electricity (OE) launched the Storage Design Strategies to Ease Production (STEP) Prize, a new competition to help the next generation of energy storage technologies move more smoothly from concept to real-world manufacturing.
DOE report shows pressing need for more electric transmission infrastructure to power a reliable and secure grid.
OE launched the Storage Design Strategies to Ease Production (STEP) Prize, a $500k competition to accelerate next-gen energy storage technologies by addressing manufacturing and supply chain challenges early in the design process.
Mission-critical commercial and military applications have extremely high uptime requirements and tight deployment space constraints. Advanced small nuclear reactors, packaged as compact units and deployed in microgrids, present a tantalizing option to meet these constraints and advance many of our nation’s priorities.
Microgrids offer a promising solution to enable the fast, reliable, and affordable build-out of data centers with shorter timelines relative to distribution/transmission grid expansion.
Microgrids have emerged as a promising part of the solution to the challenges of increasing electricity costs, power outages and increasing loads.
The power grid needs innovative ways to add additional energy production and control capabilities to the power system. The Office of Electricity is advancing one such approach with microgrid systems.
37 homes at The Medley at Southshore Bay in Tampa kept the lights on during Hurricane Ian in Florida. Their resilience was bolstered by a microgrid.
As artificial intelligence (AI) expands rapidly, large-scale data centers are becoming one of the largest and most dynamic classes of new electric loads. Unlike regular data centers with relatively constant demands for power, AI training centers use thousands of specialized computer chips that work together in tightly coordinated cycles.