8 citations · 17 across the 10 of their papers we have counts for
6 papers · 1 filter
Physics-Informed AI Inverter
Qing Shen, Yifan Zhou, Peng Zhang +3
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 in…
Software-Defined Virtual Synchronous Condenser
Zimin Jiang, Peng Zhang, Yifan Zhou +6
Synchronous condensers (SCs) play important roles in integrating wind energy into relatively weak power grids. However, the design of SCs usually depends on specific application re…
Physics-Aware Neural Dynamic Equivalence of Power Systems
Qing Shen, Yifan Zhou, Qiang Zhang +3
This letter devises Neural Dynamic Equivalence (NeuDyE), which explores physics-aware machine learning and neural-ordinary-differential-equations (ODE-Net) to discover a dynamic eq…
Scalable Neural Dynamic Equivalence for Power Systems
Qing Shen, Yifan Zhou, Huanfeng Zhao +4
Traditional grid analytics are model-based, relying strongly on accurate models of power systems, especially the dynamic models of generators, controllers, loads and other dynamic…
Neuro-Dynamic State Estimation for Networked Microgrids
Fei Feng, Yifan Zhou, Peng Zhang
We devise neuro-dynamic state estimation (Neuro-DSE), a learning-based dynamic state estimation (DSE) algorithm for networked microgrids (NMs) under unknown subsystems. Our contrib…
Neuro-Reachability of Networked Microgrids
Yifan Zhou, Peng Zhang
A neural ordinary differential equations network (ODE-Net)-enabled reachability method (Neuro-Reachability) is devised for the dynamic verification of networked microgrids (NMs) wi…