Researchers simulated the wind damage from seven historical hurricanes to identify just a few key electrical lines that were crucial to protect the whole grid from cascading power failures
By Jeremy Hsu
12 March 2024
The damage from storms like Hurricane Harvey caused serious blackouts to the Texas power grid
Mark Ralston/AFP via Getty Images
Storm-proofing as little as 1 per cent of the power lines in an electricity grid could slash the chance of hurricane-induced blackouts by between fivefold and 20-fold, a simulation suggests. The demonstration, which took place in a simulated version of the Texas electricity grid, could help boost the resilience of power transmission systems worldwide.
“The importance of various lines to the overall system only becomes apparent if we study the partially destroyed states of the grid that occur as the storm progresses,” says Frank Hellmann at the Potsdam Institute for Climate Impact Research in Germany.
To identify those critical power transmission lines most in need of protection, Hellmann and his colleagues examined how the grid responds to widespread damage over time. They focused on large “failure cascades” that occur after the initial storm damage: as power plants and transmission lines shut off to protect themselves from additional damage, they cause secondary power outages that can broaden the hurricane’s impact.
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The researchers simulated both wind-related storm damage – such as gusts damaging towers or taking down tree branches that fall onto transmission lines – and the resulting cascade of power outages that occurred in the Texas power grid during seven historical hurricanes between 2003 and 2020.
Instead of trying to predict individual power line failures that can occur from a fallen tree or a lightning strike, the researchers assigned each line a probability of failure based on local wind speeds during each storm event. Their model consistently identified the same 20 critical lines where initial storm damage could trigger a cascade of secondary line failures – even when they reran the simulation with random variations in each line’s probability of failure.