How artificial intelligence can stop grid cyber-attacks and over-load

A  team of scientists say they can predict attacks and blackouts, making the grid more resilient –– and they are using AI.

The post How artificial intelligence can stop grid cyber-attacks and over-load appeared first on Green Prophet.

 

 

 

 

 

 

 

 

 

 

 

AI could be the key to protecting our solar-powered future — making grids smarter, safer, and resilient against blackouts and cyberattacks.

Elon Musk has been saying it for years and it’s something that solar power pioneers already know: the sun has enough energy to power all of our energy needs. The problem is limited not only by making sure that people get the technology to harvest the sun on solar panels, but in cities and urban centers one of the biggest issues is storage and what to do with a surplus of energy when the sun shines? Consumers and businesses, when they can, typically shoot back the energy to the grid where they earn money or credits for what they’ve contributed.

But electricity grids can’t always handle excessive or varying amounts of energy. It’s a complicated switchboard that can be overloaded during extreme heat waves when everyone turns on their air conditioners. Energy managers want to make the grids most efficient and mixed with the least carbon intensive energy sources, but how? And what about cyber attacks that can bring down an entire nation’s power like what happened in Spain and Portugal this year. A  team of scientists say they can predict attacks and blackouts, making the grid more resilient –– and they are using AI.

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Researchers at Sandia National Laboratories have developed brain-inspired AI algorithms that detect physical problems, cyberattacks and both at the same time within the grid. And this neural-network AI can run on inexpensive single-board computers or existing smart grid devices.

“As more disturbances occur, whether from extreme weather or from cyberattacks, the most important thing is that operators maintain the function and reliability of the grid,” said Shamina Hossain-McKenzie, a cybersecurity expert and leader of the project. “Our technology will allow the operators to detect any issues faster so that they can mitigate them faster with AI.”

The importance of cyber-physical protection

As the United States adds more smart controls and devices to the grid, it becomes more flexible and autonomous but also more vulnerable to cyberattacks and cyber-physical attacks. Cyber-physical attacks use communications networks or other cyber systems to disrupt or control a physical system such as the electric grid. Potentially vulnerable equipment includes smart inverters that turn the direct current produced by solar panels and wind turbines into the alternating current used by the grid, and network switches that provide secure communication for grid operators, said Adrian Chavez, a cybersecurity expert involved in the project.

Because the neural network can run on single-board computers, or existing smart grid devices, it can protect older equipment as well as the latest equipment that lack only cyber-physical coordination, Hossain-McKenzie said.

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“To make the technology more accessible and feasible to deploy, we wanted to make sure our solution was scalable, portable and cost-efficient,” Chavez said.

The package of code works at the local, enclave and global levels. At the local level, the code monitors for abnormalities at the specific device where it is installed. At the enclave level, devices in the same network share data and alerts to provide the operator with better information on whether the issue is localized or happening in multiple places, Hossain-McKenzie said.