No, a single point of failure means that everything depends on a single thing. I.e. if you've got 10 gas engines all being fed by a single pipeline. Or a single powerline providing all electricity to the full grid.
That pipeline/powerline is your single point of failure.
It is still a single network, but you need multiple failures to manifest into a cascading issue like this.
What you're probably thinking of is more akin to distributed system which fails when any one component fails, i.e. modern microservice architectures, aka distributed monoliths. But that's not the case here, because you constantly have minor issues on the grid. They're just continuously being handled. What becomes the issue is the cascade, with each failure increasing the likelihood of a following failure etc.
In web developer terms, this is as if a production k8s cluster fails because a node went offline, which rebalanced too many containers to another node which ran out of memory, causing it to crash and starting the cascade, ultimately ending with adjacent clusters starting to crash because of the error quotas etc
That pipeline/powerline is your single point of failure.
It is still a single network, but you need multiple failures to manifest into a cascading issue like this.
What you're probably thinking of is more akin to distributed system which fails when any one component fails, i.e. modern microservice architectures, aka distributed monoliths. But that's not the case here, because you constantly have minor issues on the grid. They're just continuously being handled. What becomes the issue is the cascade, with each failure increasing the likelihood of a following failure etc.
In web developer terms, this is as if a production k8s cluster fails because a node went offline, which rebalanced too many containers to another node which ran out of memory, causing it to crash and starting the cascade, ultimately ending with adjacent clusters starting to crash because of the error quotas etc