5 papers
Enabling Scalable Topology Inference in Distribution Systems via Constrained Multi-Source Inference
Haoran Li, Lihao Mai, Muhao Guo +2
Accurate distribution system topology is essential for outage localization, voltage analytics, and operation of distribution grids, yet maintaining reliable connectivity records re…
Structure-Aware Commitment Reduction for Network-Constrained Unit Commitment with Solver-Preserving Guarantees
Guangwen Wang, Jiaqi Wu, Yang Weng +1
The growing number of individual generating units, hybrid resources, and security constraints has significantly increased the computational burden of network-constrained unit commi…
Graph Structure Learning with Privacy Guarantees for Open Graph Data
Muhao Guo, Jiaqi Wu, Yizheng Liao +3
Publishing open graph data while preserving individual privacy remains challenging when data publishers and data users are distinct entities. Although differential privacy (DP) pro…
A Unified Approach to Enforce Non-Negativity Constraint in Neural Network Approximation for Optimal Voltage Regulation
Jiaqi Wu, Jingyi Yuan, Yang Weng +1
Power system voltage regulation is crucial to maintain power quality while integrating intermittent renewable resources in distribution grids. However, the system model on the grid…
From Imperfect Signals to Trustworthy Structure: Confidence-Aware Inference from Heterogeneous and Reliability-Varying Utility Data
Haoran Li, Lihao Mai, Muhao Guo +4
Accurate distribution grid topology is essential for reliable modern grid operations. However, real-world utility data originates from multiple sources with varying characteristics…