“For example, you could see where vegetation is growing with respect to the power lines, and anticipate when trees are likely to grow over the power lines and pull them over during a storm.” The US Department of Energy’s (DOE) SLAC National Accelerator Laboratory will lead a three-year project using artificial intelligence and machine learning to reinforce the grid, enabling it to automatically deal with power fluctuations or external weather events. The $6m Grid Resilience and Intelligence Project (GRIP), is part of the DOE’s Grid Modernisation Initiative, and will use satellite imagery, utility operations and other sources to develop machine learning algorithms, based on how electrical distribution systems function. GRIP aims to help utilities better understand their own grid operations, identify vulnerabilities in them and improve resilience against them.
The US Department of Energy’s (DOE) SLAC National Accelerator Laboratory will lead a three-year project using artificial intelligence and machine learning to reinforce the grid, enabling it to automatically deal with power fluctuations or external weather events. The $6m Grid Resilience and Intelligence Project (GRIP), is part of the DOE’s Grid Modernisation Initiative, and will use satellite imagery, utility operations and other sources to develop machine learning algorithms, based on how electrical distribution systems function. GRIP aims to help utilities better understand their own grid operations, identify vulnerabilities in them and improve resilience against them.