Numerical Methods

Neural Substitute Solver for Efficient Edge Inference of Power Electronic Hybrid Dynamics
NSS enables fast, low-cost edge inference of hybrid PES dynamics by replacing traditional solvers with parallel-friendly neural networks, achieving 23× speedup and 60% resource savings.
Jialin Zheng, Haoyu Wang, Yangbin Zeng, Han Xu, Di Mou, Hong Li, Sergio Vazquez, Leopoldo G. Franquelo
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Neural Substitute Solver for Efficient Edge Inference of Power Electronic Hybrid Dynamics
Topology-Aware Iterative Method for Large-scale Power Electronic Systems with Stray Parameters
Power electronic systems are crucial in modern power grids. Accurate offline simulation tools are essential for analyzing such systems. …
Han Xu, Zhengming Zhao, Bochen Shi, Yangbin Zeng, Jialin Zheng, Weicheng Liu, Di Mou, Haoyu Wang
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An Event-Driven Real-Time Simulation for Power Electronics Systems Based on Discrete Hybrid Time-Step Algorithm
This paper presents an innovative event-driven real-time simulation framework for power electronic systems, significantly enhancing simulation efficiency and accuracy while reducing hardware costs.
Jialin Zheng, Zhengming Zhao, Yangbin Zeng, Bochen Shi, Zhujun Yu
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An Event-Driven Real-Time Simulation for Power Electronics Systems Based on Discrete Hybrid Time-Step Algorithm
An Event-Driven Parallel Acceleration Real-Time Simulation for Power Electronic Systems Without Simulation Distortion in Circuit Partitioning
This paper introduces an innovative ED-HIL simulation framework and a PACP solver, significantly enhancing the real-time simulation capabilities of power electronic systems.
Jialin Zheng, Zhengming Zhao, Yangbin Zeng, Shiqi Ji, Liqiang Yuan
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An Event-Driven Parallel Acceleration Real-Time Simulation for Power Electronic Systems Without Simulation Distortion in Circuit Partitioning