The electric grid faces challenges as new energy technologies and resources are added to meet rising energy demand. To ensure grid reliability into the future, we need advanced integration, including grid modernization.

Grid integration of renewable energy means optimizing operations and planning for a reliable and affordable electricity system that uses a variety of energy generators. This includes where generators are built, how they are optimized, and how they are used to power the 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 reliable, efficient performance. For example, better projections of water availability can help maximize generation at hydropower facilities. It also includes advanced modeling and simulation to understand the operational connections governing energy availability, generator performance, grid reliability, and electricity delivery to customers.

Grid integration of renewable energy also involves overcoming challenges such as instantaneous to seasonal fluctuations of energy resources. By developing solutions and mitigative measures across both information technology and operational technology systems, we can achieve more reliable, affordable energy. 

PNNL’s grid integration research includes:

• Developing modeling, control, and optimization capabilities for renewable resources on the power grid, leveraging power electronics and data analytics capabilities
• Analyzing renewable energy system performance using advanced prediction capabilities
• Advancing prediction capabilities to support planning and operations under a variety of conditions (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 reliability, along with reducing costs 
• Analyzing energy systems at multiple scales and parts of the grid for planning and optimization
• Developing market frameworks that encompass the full range of available energy services and costs 
• Evaluating models, data, costs, and assumptions within grid and utility processes to streamline interconnection and inform integration of new energy technology.