  Smart grids are critical cyber-physical systems that are vital to our energy
future. Smart grids' fault resilience is dependent on the use of advanced
protection systems that can reliably adapt to changing conditions within the
grid. The vast amount of operational data generated and collected in smart
grids can be used to develop these protection systems. However, given the
safety-criticality of protection, the algorithms used to analyze this data must
be stable, transparent, and easily interpretable to ensure the reliability of
the protection decisions. Additionally, the protection decisions must be fast,
selective, simple, and reliable. To address these challenges, this paper
proposes a data-driven protection strategy, based on Gaussian Discriminant
Analysis, for fault detection and isolation. This strategy minimizes the
communication requirements for time-inverse relays, facilitates their
coordination, and optimizes their settings. The interpretability of the
protection decisions is a key focus of this paper. The method is demonstrated
by showing how it can protect the medium-voltage CIGRE network as it
transitions between islanded and grid-connected modes, and radial and mesh
topologies.
