2017/08/01 by Mahdi Jamei, Jamei, Mahdi, Anna Scaglione +11
Engineering · #Data Analysis #FOS: Electrical engineering #FOS: Physical sciences #Power System Optimization and Stability #Power Systems Fault Detection #Smart Grid Security and Resilience #Statistics and Probability (physics.data-an) #Systems and Control (eess.SY) #electronic engineering #information engineering
paper · pdf · doi:10.48550/arxiv.1708.00118
openalex publication_date 2017/08/01 · openalex created_date 2019/06/27 · openalex updated_date 2026/08/01
As the distribution grid moves toward a tightly-monitored network, it is important to automate the analysis of the enormous amount of data produced by the sensors to increase the operators situational awareness about the system. In this paper, focusing on Micro-Phasor Measurement Unit (μPMU) data, we propose a hierarchical architecture for monitoring the grid and establish a set of analytics and sensor fusion primitives for the detection of abnormal behavior in the control perimeter. Due to the key role of the μPMU devices in our architecture, a source-constrained optimal μPMU placement is also described that finds the best location of the devices with respect to our rules. The effectiveness of the proposed methods are tested through the synthetic and real μPMU data.