The N-1 principle
Given the problems on grid capacity and contingency, the complexity of the power grid is increasing. Grid operators must ensure that the power grid remains reliable, even when a power cable fails. This is called the 'n-1 principle': in case of a failure, electricity must be able to be rerouted through alternative paths without causing problems.
During such rerouting, the load on alternative routes increases. Therefore, it is crucial to test whether these routes can handle the extra load. This involves checking not only the capacity of the cables but also whether the voltage and current and network stability remain within safe limits. Until now, for optimal results, the grid operators relied on mathematical calculations that checked all possible rerouting paths one by one - a process that could take hours.
The new approach
The new technology, developed by researcher Charlotte Cambier van Nooten and colleagues, uses machine learning. They have developed a 'Graph Neural Network' (GNN) specifically adapted for power grids. This method views the entire network as a whole, rather than examining each route separately. Additionally, the method takes into account the properties of both the cables and the nodes in its calculations. The system learns to recognize patterns and works even for situations it has never encountered before.
Charlotte Cambier van Nooten: "When there's a failure, you want to quickly know the best method to solve it. Our new method can do this in seconds. Moreover, our method is on average 5% more accurate than traditional methods."
From research to practice
The method has been tested on the medium-voltage grid, a complex cable network that delivers electricity between different substations. Grid operator Alliander has already begun implementing this new technology.
