AIMS: Autonomous Intelligent Measurement Sensing and Systems

Drone-based sensing for electric grid inspection

A reliable, resilient power grid is key to community health and safety, economic security, and quality of life. The Grid Communications and Security group is integrating sensing and communications platforms to support grid reliability through power line inspection and rapid response to unusual grid behavior. 

These efforts are the cornerstone of a project incorporating drone-based sensors and associated technologies, called Autonomous Intelligent Measurement Sensors and systems, or AIMS. The approach uses machine-to-machine communications to automatically sense problems, generate work orders, and coordinate multi-stage drone inspection of electrical transmission equipment. Researchers customized off-the-shelf drones, sensors and software, and developed new technology, algorithms, and automated protocols so the gathered data can be used in real-time decision making.

The system enables utility supervisory control and data acquisition (SCADA) systems to automatically respond to abnormal sensor or equipment readings by dispatching drones from substations. Flying semi-autonomously using global positioning and obstacle-avoidance technology, the drones can carry sensors such as visible, ultraviolet and infrared cameras, microphones, and radio frequency or electromagnetic detectors. Even in areas with limited road access, drones can travel to the source location, gather information, and transmit relevant data in real-time.

AIMS utilizes generative artificial intelligence, or AI, techniques to analyze partial information sets obtained from a variety of drone-based sensors and systems. By comparing and integrating interpreted measurements from different classes of sensors, the AI analysis determines a utility’s optimal response to unusual events in the grid.

The AIMS system is intended to increase worker and community safety and improve response times, while saving utility resources. It can provide both routine monitoring and rapid response to unusual operating conditions such as storm damage. Using advanced transducers, multi-phase communications, and data analysis, AIMS prevents wildfires by identifying and addressing risks such as equipment overheating or electrical arcing. AIMS enhances grid security by providing increased situational awareness in the face of increasingly frequent natural disasters and attacks on grid equipment.

ORNL researchers are demonstrating the use of the AIMS platform to inspect a variety of energy assets, from transmission lines to solar farms and hydroelectric dams. The demonstrations and partner feedback will enable ORNL researchers to enhance the platform’s usability, effectiveness, and performance for seamless integration into a variety of commercially-available systems, so the benefits can become rapidly available to utilities. 

The Grid Communications and Security group has extensive experience in developing airborne sensor platforms, ranging from drones to high-altitude balloons and long-endurance aircraft. Among recent efforts, researchers supported wildland firefighters through the development of drone-based sensing systems for detecting and tracking wildfires. The group has its own drone-flight operations team.