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arXiv · 2406.17661

Physics-Informed AI Inverter

Qing Shen·Yifan Zhou·Peng Zhang·Yacov A. Shamash·Roshan Sharma·Bo Chen
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Abstract

This letter devises an AI-Inverter that pilots the use of a physics-informed neural network (PINN) to enable AI-based electromagnetic transient simulations (EMT) of grid-forming inverters. The contributions are threefold: (1) A PINN-enabled AI-Inverter is formulated; (2) An enhanced learning strategy, balanced-adaptive PINN, is devised; (3) extensive validations and comparative analysis of the accuracy and efficiency of AI-Inverter are made to show its superiority over the classical electromagnetic transient programs (EMTP).

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Qing Shen, Yifan Zhou, Peng Zhang, Yacov A. Shamash, Roshan Sharma, Bo Chen. 2024-06-25. Physics-Informed AI Inverter. https://arxiv.org/abs/2406.17661

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