Situational Awareness Using DBSCAN in Smart-Grid

Synchrophasors are the state-of-the-art measuring devices that sense various parameters such as voltage, current, frequency, and other grid parameters with a high sampling rate. This paper presents an approach to visualize and analyze the smart-grid data generated by synchrophasors using a visualization tool and density based clustering technique. A MATLAB based circle representation tool is utilized to visualize the real-time phasor data generated by a smart-grid model that mimics a synchrophasor. A density based clustering technique is also used to cluster the phasor data with the aim to detect contingency situations such as bad-data classification, various fault types, deviation on frequency, voltage or current values for better situational alertness. The paper uses data from an IEEE fourteen bus system test-bed modeled in MATLAB/SIMULINK to aid system operators in carrying various predictive analytics, and decisions.