{'fraction_non_alphanumeric': 0.02048780487804878, 'fraction_numerical': 0.0, 'mean_word_length': 5.9324324324324325, 'pattern_counts': {'":': 0, '<': 0, '<?xml version=': 0, '>': 0, 'https://': 0, 'lorem ipsum': 0, 'www.': 0, 'xml': 0}, 'pii_count': 0, 'substrings_counts': 0, 'word_list_counts': {'cursed_substrings.json': 0, 'profanity_word_list.json': 0, 'sexual_word_list.json': 0, 'zh_pornsignals.json': 0}}
Two-Stage Parallel Waveform Relaxation Method for Large-Scale Power System Transient Stability Simulation

This work presents a parallel transient stability simulation based on waveform relaxation for large-scale power systems. A power system described by large-scale differential-algebraic equations (DAE) is decomposed into several subsystems by a partitioning algorithm based on epsilon decomposition. The method adopts preconditioning and waveform prediction to accelerate convergence of the system. Moreover, a two-stage parallel strategy based on OpenMP further improves parallel efficiency. All subsystems are solved using a very dishonest Newton (VDHN) method combined with an iteration method based on Adomian decomposition independently after the state variables are discretized by implicit-trapezoidal rule. Finally, two large-scale test cases with detailed dynamic models verify the proposed algorithm. The computational results show that the proposed waveform relaxation method achieves high parallel efficiency.