38 citations · 42 across the 4 of their papers we have counts for
9 papers
Dimensionality Increment of PMU Data for Anomaly Detection in Low Observability Power Systems
Xin Shi, Robert Qiu
Anomaly detection is an important task in power systems. To make better use of the phasor measurement unit (PMU) data collected from a low observability power system for anomaly de…
Early Anomaly Detection in Power Systems Based on Random Matrix Theory
Xin Shi, Robert Qiu
It is important for detecting the anomaly in power systems before it expands and causes serious faults such as power failures or system blackout. With the deployments of phasor mea…
Short-term Electric Load Forecasting Using TensorFlow and Deep Auto-Encoders
Xin Shi
This paper conducts research on the short-term electric load forecast method under the background of big data. It builds a new electric load forecast model based on Deep Auto-Encod…
Estimation of high-dimensional factor models and its application in power data analysis
Xin Shi, Robert Qiu
In dealing with high-dimensional data, factor models are often used for reducing dimensions and extracting relevant information. The spectrum of covariance matrices from power data…
Improving Power System State Estimation Based on Matrix-Level Cleaning
Haosen Yang, Robert C. Qiu, Lei Chu +3
Power system state estimation is heavily subjected to measurement error, which comes from the noise of measuring instruments, communication noise, and some unclear randomness. Trad…
Spatio-Temporal Correlation Analysis of Online Monitoring Data for Anomaly Detection and Location in Distribution Networks
Xin Shi, Robert Qiu, Zenan Ling +3
The online monitoring data in distribution networks contain rich information on the running states of the networks. By leveraging the data, this paper proposes a spatio-temporal co…