Power System Data Analytics
Several studies have been conducted based on historical data from the Frequency Monitoring Network (FNET/GridEye) to better analyze and interpret the information contained in the large volume of data. Partial results are included here and readers can refer to the corresponding references for more details. First, the frequency distribution pattern work investigates the probability distribution of ambient frequency data under different years, seasons and the daily load conditions for major worldwide power grids . This can help identify the possible factors that impact the power system frequency distribution patterns. Figure 1 shows the frequency distribution of EI in summer. Second, the distributions of disturbance sizes and frequency changes were analyzed. This information can facilitate the modeling, operation and planning of the power system . Figure 2 illustrates the log-log curve of disturbances, lognormal distribution for small disturbances and power law distribution for large disturbances. It can be observed that the megawatt size of disturbances can be delineated with log-normal distribution for small disturbances and power law distribution for large disturbances. Third, a method to estimate the system inertia using historical measurement data was developed  and the effects of different factors, such as system load and seasonal variation, on the system inertia were also investigated. Figure 3 shows that the relationship between inertial frequency response and generation loss is highly correlated. Finally, the stored oscillation data in FNET/GridEye database were analyzed to better understand the distribution of oscillation mode frequency, damping ratio and magnitude.
 P. N. Markham, Y. Liu, T. Bilke and D. Bertagnolli, “Analysis of Frequency Extrema in the Eastern and Western Interconnections,” in Proc. 2011 IEEE Power and Energy Society General Meeting, pp.1-8, 24-29 July 2011.
 L. Liu, J. Chai, H. Qi and Y. Liu, “Power Grid Disturbance Analysis Using Frequency Information at the Distribution Level,” in Proc. 2014 IEEE International Conference on Smart Grid Communications, Nov. 2014.
 D.P. Chassin, Z. Huang, M.K. Donnelly, C. Hassler, E. Ramirez, and C. Ray, “Estimation of WECC System Inertia Using Observed Frequency Transients”, IEEE Trans. Power Systems, vol. 20, no. 2, pp. 1190-1192, May 2005.