What adaptive neuronal networks teach us about power grids

Power grid networks, as well as neuronal networks with synaptic plasticity, describe real-world systems of tremendous importance for our daily life. We provide insight into the fundamental relation between these two types of networks by proving that phase oscillator models with inertia can be viewed as a particular class of adaptive networks. As an immediate consequence of the unification, we find a novel type of multicluster state for phase oscillators with inertia and the emergence of solitary nodes (see also Figure 1). Moreover, the phenomenon of cascading line failures in power grids is translated into a neuronal model of adaptively coupled phase oscillators.