Localized diakoptic refactorization for MNA-based EMT and DP power system simulations

Electromagnetic-transient (EMT) as well as Dynamic-Phasor (DP) simulations of power system stability events using Modified Nodal Analysis (MNA) need repeated factorization of large sparse matrices whenever topology changes occur—such as short circuit faults, line protection tripping and voltage induced tripping of generators or loads. Traditional approaches rebuild the full system matrix at each event or precompute and factorize system matrices based on anticipated switching events. In this paper we propose a network tearing (diakoptics) approach that partitions the system into subnetworks, recomputing only the MNA blocks associated with topology changes. Previous studies have already shown that parallelizing simulation steps within the diakoptics framework can significantly improve performance. In this work, we show that diakoptics offers performance benefits even without parallelization, as only the matrix blocks affected need to be refactorized for topology changes. We validate our approach against full-system MNA solutions for both EMT and DP simulations and present results quantifying performance improvements and scalability across different network sizes and partitioning granularities.