Category: Nonlinear Dyn.

Summary: Testing whether adaptive reclosure thresholds improve service and synchrony after islanding events in a power-grid-like Kuramoto network before fatigue makes repeated action harmful.

Power-grid failures often involve temporary islanding, load shedding, and attempts to reclose disconnected regions. This experiment models that process with Kuramoto-style phase dynamics and asks whether there is a threshold window where adaptive reclosure improves recovery without triggering too much fatigue or instability.

The code simulates trip and reclose events, compares mean served load, synchronization order, and shedding under different thresholds, and summarizes the re-entrant gain from adaptive intervention. The emphasis is on whether moderate action helps more than aggressive or minimal reclosure.

That framing matters because restoration is not a one-shot choice. Repeated switching can itself be costly, so the interesting question is when adaptive reclosure is truly beneficial rather than simply more active.

Method: Kuramoto-based grid-islanding simulations with adaptive reclosure thresholds, aggregated over repeated stochastic trials.

What is measured: Re-entrant gain, served-load fraction, synchronization order, shedding, trip events, reclose events, support fraction, and best threshold.