Lawrence Livermore National Laboratory

LLNL is applying systems engineering, high-performance computing, and data analytics to enabling the secure, resilient, reliable, and sustainable design and operation of the nation's infrastructure systems.

  • Advanced infrastructure modeling and simulation
  • Infrastructure data informatics
  • Distributed energy resource integration
  • Risk and resilience

See our Community Energy Solutions for more information about how partnering with LLNL can bring solutions to community energy needs.

diagram showing power going in and out in electrical transmission and distribution systems.

Interconnection between transmission and distribution systems in the grid—a key missing link in current models.

 Grid Modernization Laboratory Consortium logo.

Grid Modernization Projects

The Laboratory is part of the DOE Grid Modernization Laboratory Consortium, which is conducting critical research and development in advanced storage systems, clean energy integration, standards and test procedures, and a number of other key grid modernization areas. LLNL has a leadership role on the following projects:

Advanced Grid Modeling

Supporting the Office of Electricity’s (OE) Advanced Grid Modeling (AGM) program in advancing technologies in the areas of the 1) Data Management and Analytics, 2) Mathematical Methods and Computation, 3) Models and Simulation, and 4) Operator Tools and Decision Support, to help address the challenges in power grid planning and operation.

Integrated Multi Scale Data Analytics and Machine Learning for the Grid

Creating advanced, distributed data analytics capability to provide visibility and controllability to distribution grid and building operators.

Multi-Scale Integration of Control Systems

Creating an integrated grid management framework akin to having an autopilot system for the grid's interconnected components.

Development of Integrated Transmission, Distribution and Communication Models

Creating a flexible and scalable open-source co-simulation framework that can simulate regional and interconnection-scale power system behaviors at unprecedented levels of detail and speed.

Threat Detection and Response with Data Analytics

Developing advanced analytics on operational technology cyber data in order to detect complex cyber threats in the power grid.


Validating and demonstrating, at scale, a distributed-energy-resources-driven mitigation, blackstart, and restoration strategy for distribution feeders.