6 papers
Network Interdependency-Informed Power System Dynamic Trajectory Prediction Utilizing Black-Box Modeling of Multiple Inverter-Based Resources
Sungjoo Chung, Ying Zhang, Meng Yue +1
Black-box modeling of inverter-based resources (IBRs) has attracted growing interest for real-time grid operation and control in the presence of proprietary electronic control arch…
Utilizing Adversarial Training for Robust Voltage Control: An Adaptive Deep Reinforcement Learning Method
Sungjoo Chung, Ying Zhang
Adversarial training is a defense method that trains machine learning models on intentionally perturbed attack inputs, so they learn to be robust against adversarial examples. This…
On the Potential of Digital Twins for Distribution System State Estimation with Randomly Missing Data in Heterogeneous Measurements
Ying Zhang, Yihao Wang, Yuanshuo Zhang +3
Traditional statistical optimization-based state estimation (DSSE) algorithms rely on detailed grid parameters and mathematical assumptions of all possible uncertainties. Furthermo…
Impact of Solar Integration on Grid Security: Unveiling Vulnerabilities in Load Redistribution Attacks
Praveen Verma, Di Shi, Yanzhu Ye +2
Load redistribution (LR) attacks represent a practical and sophisticated form of false data injection (FDI) attacks, where the attacker manipulates grid data to influence economic…
A Virtual Admittance-Based Fault Current Limiting Method for Grid-Forming Inverters
Zaid Ibn Mahmood, Hantao Cui, Ying Zhang
Inverter-based resources (IBRs) are a key component in the ongoing modernization of power systems, with grid-forming (GFM) inverters playing a central role. Effective fault current…
Taylor-Expansion-Based Robust Power Flow in Unbalanced Distribution Systems: A Hybrid Data-Aided Method
Sungjoo Chung, Ying Zhang, Zhaoyu Wang +1
Traditional power flow methods often adopt certain assumptions designed for passive balanced distribution systems, thus lacking practicality for unbalanced operation. Moreover, the…