The ORNL Grid Operations and Analytics Laboratory, or GOAL, is a test bed for monitoring and use of data from control and operations of public utilities and other facilities, to improve the overall resilience and security of the nation’s electric grid. GOAL expertise encompasses sensor development and deployment as well as security innovations and algorithms. These innovations enable recognition and reduction of physical and cyber risks, protecting not only the grid but other types of infrastructure, such as transportation. Research activities emanate from the lab to include field locations such as utility partner facilities.
Uniqueness and capabilities
Advancing drone-based sensing and recording capabilities to better identify and respond to maintenance needs and grid failures in remote areas; to locate external threats such as heat and fire that could damage electrical equipment; and to safeguard the health of first responders.
Innovating new security approaches to protect communications among devices and within the automation/management systems used by utilities and industrial facilities.
Developing sensors and algorithms for: recognizing arcing and measuring risk to power electronics equipment and transmission lines; finding wildfires; detecting potentially harmful airborne particulates and chemicals; and enhancing viability, range, and efficiency of electric vehicles. The lab provides real-time visualization of sensor data.
Designing and testing novel sensing and measurement tools such as a radio telescope for understanding solar emissions in the 12 GHz radio band and eventual detection of millisecond-rotation pulsar emissions.
Technology resources
10GB fiber optic link with electric utility research partner EPB of Chattanooga for real-world, real-time data feeds
A variety of unmanned aerial systems with associated/qualified operating crews
Replicated utility command center with associated display walls, graphic application interfaces for tracking real-time outages and other data, and associated components
Grid Signature Library: Catalogue of waveform datasets representing both live sensor data and events recorded during grid operations, incorporating machine learning for waveform signature identification and matching
Enhanced data security layers and connectivity with Alternate Timing and Synchronization Laboratory in GRID-C
