RAPTOR: RAndom-projection Physics-informed Transient sOlveR

RAPTOR is a novel time‑domain simulation framework for power systems that uses a physics‑informed random‑projection neural network built from fixed Gaussian radial basis functions to represent the trajectory of hybrid differential‑algebraic equations over a time interval. By combining these basis functions with a nonlinear solver such as Newton‑Raphson, RAPTOR can capture complex multi‑timescale dynamics over longer intervals, reducing the number of simulation advances and nonlinear iterations needed. Numerical tests on RMS and EMT benchmarks demonstrate that RAPTOR achieves accurate solutions with significantly fewer steps and can outperform traditional methods like Radau and the trapezoidal rule, achieving speedups of over tenfold in some cases.