Without a reliable metering and communication infrastructure, the smart grid could become a catastrophe to national security and economy. A true smart grid infrastructure should detect all existing and predict future threats through intrusion detection methods. Smart grids are susceptible to various physical and cyber-attack as a result of communication, control and computation vulnerabilities employed in the grid. The paper provides a comprehensive study on types of threats and solutions on smart grid communication and metering infrastructures. As a part of this survey, the smart grid metering infrastructures susceptibilities and recommended remedial actions are identified. In addition, the paper details types of known attacks on existing metering infrastructure and defensive methodologies.

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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.

This paper presents a density based clustering (DBSCAN) technique to visualize and analyze the smart-grid data. The technique will aid in detecting bad-data, various fault types, deviation on frequency, voltage or current values for better situational awareness. Synchrophasors (or a PMU) is a sensor placed on a transmission line that tracks voltage, current, phase and frequency of the line. To improve situational awareness of the smart grid monitoring in real-time, the utility must monitor the phasor data measurement delivered by the sensors. Time-stamped synchronized measurements offer tremendous benefit for pre and post-event analysis. The paper uses data from openPDC framework to aid system operators in carrying various predictive analytics, decisions.