With the growth of renewable energy, the electric grid is shifting. To make sure the grid is ready to meet the rising tide of clean energy technologies, advanced integration—including grid modernization and visions for future designs—is needed.

Grid integration of renewable energy means reimagining operation and planning for a reliable, cost-effective, and efficient electricity system with cleaner new energy generators. This includes where it is built, how it is optimized, and how it is used to power a carbon-free future. It means providing grid operators with the situational awareness and control capabilities they need to plan and manage a rapidly changing energy resource mix.

The path forward involves assessing long-range demands and evaluating pathways for efficient performance. For example, projecting atmospheric patterns can help guide—and maximize—siting of solar or wind power. It also includes evaluating, scheduling, and optimizing future energy market design using advanced modeling and simulation to understand the operational connections to renewable energy availability, generator performance, grid reliability, and electricity delivery to customers.

Grid integration of renewable energy includes building resilience against threats, such as natural disasters and cyberthreats. It also involves overcoming challenges, such as instantaneous to seasonal unavailability of renewable resources. By developing solutions and mitigative measures across both information technology and operational technology systems, we can prepare for a cleaner, greener, and more resilient energy landscape.

Renewable-grid integration for a carbon-free future

Pacific Northwest National Laboratory is committed to being the national research and development leader in helping the nation build a cleaner, more resilient, and more secure power grid. Our work in the grid integration area includes:

• Developing modeling, control, and optimization capabilities for the renewable-dominated power grid, leveraging power electronics and data analytics capabilities
• Analyzing renewable energy system performance using advanced prediction capabilities
• Advancing prediction capabilities to support the evolution of networks to withstand extreme events (e.g., wildfires, tsunamis, hurricanes, or cyber-attacks) or asynchronous supplies
• Assessing locational value within the grid, with a focus on novel technologies where the value is not well understood or represented
• Optimizing interconnected technologies (e.g., generator, electric load, and storage) at a variety of scales to improve operations and efficiency, along with reducing costs and need for peaking or emitting facilities
• Analyzing meter-, microgrid-, feeder-, substation-, and community-scale networks for planning and optimization
• Developing new economic frameworks that encompass a full range of renewable energy services and costs rather than a focus on traditional energy resources
• Evaluating models, data, costs, and assumptions within grid and utility processes to assure equitable treatment, reasonable time, and cost for interconnection and to inform how technology can be designed and validated for more effective integration.