8 citations · 10 across the 4 of their papers we have counts for
5 papers
Identifiability-Guided Composite Load Modeling of AI Data Centers
Ding Lin, Jianhui Wang, Meng Yue +1
The rapid growth of AI data centers introduces large, workload-dependent loads whose protection and reconnection behavior can affect power-system transient stability. Calibrating d…
Task-Conditional Faithfulness Auditing of Multimodal LLMs for Grid Diagnosis
Tianqiao Zhao, Meng Yue, Jianhui Wang
Multimodal large language models (LLMs) can combine topology, measurements, and incident text for grid diagnosis, yet answer accuracy does not establish that task-appropriate evide…
A Deep Reinforcement Learning Method for Multi-objective Transmission Switching
Ding Lin, Jianhui Wang, Tianqiao Zhao +1
Transmission switching is a well-established approach primarily applied to minimize operational costs through strategic network reconfiguration. However, exclusive focus on cost re…
Deep Generative Graph Distribution Learning for Synthetic Power Grids
Mahdi Khodayar, Jianhui Wang, Zhaoyu Wang
Power system studies require the topological structures of real-world power networks; however, such data is confidential due to important security concerns. Thus, power grid synthe…
Convolutional Graph Auto-encoder: A Deep Generative Neural Architecture for Probabilistic Spatio-temporal Solar Irradiance Forecasting
Mahdi Khodayar, Saeed Mohammadi, Mohammad Khodayar +2
Machine Learning on graph-structured data is an important and omnipresent task for a vast variety of applications including anomaly detection and dynamic network analysis. In this…