5 papers
Synthetic Power Flow Data Generation Using Physics-Informed Denoising Diffusion Probabilistic Models
Junfei Wang, Darshana Upadhyay, Marzia Zaman +1
Many data-driven modules in smart grid rely on access to high-quality power flow data; however, real-world data are often limited due to privacy and operational constraints. This p…
Generator Cost Coefficients Inference Attack via Exploitation of Locational Marginal Prices in Smart Grid
Junfei Wang, Pirathayini Srikantha
Real-time price signals and power generation levels (disaggregated or aggregated) are commonly made available to the public by Independent System Operators (ISOs) to promote effici…
A Trustworthy AIoT-enabled Localization System via Federated Learning and Blockchain
Junfei Wang, He Huang, Jingze Feng +3
There is a significant demand for indoor localization technology in smart buildings, and the most promising solution in this field is using RF sensors and fingerprinting-based meth…
Data-driven AC Optimal Power Flow with Physics-informed Learning and Calibrations
Junfei Wang, Pirathayini Srikantha
The modern power grid is witnessing a shift in operations from traditional control methods to more advanced operational mechanisms. Due to the nonconvex nature of the Alternating C…
Complex Graph Laplacian Regularizer for Inferencing Grid States
Chinthaka Dinesh, Junfei Wang, Gene Cheung +1
In order to maintain stable grid operations, system monitoring and control processes require the computation of grid states (e.g. voltage magnitude and angles) at high granularity.…