Event Detection From PMU Generated Big Data using R Programming

Recent advancement in Power System Analysis shows that implementation of PMU (Phasor Measurement Unit) in Smart Grid playing a significant role over SCADA. The main reasoning for that is more sampling data than traditional SCADA system. Every PMU data like voltage, current and Phase angle gives more samples in every second which is helpful for event detection. The enormous data send by each PMU in every second energies the big data issue. To find out and predict the transient situation and even small disturbances or anomalies from big data analysis within the specified short period of time is a challenge for near future. Because introduction of new smart electrical devices will boost up the big data issue. Processing of big data for post disturbance analysis is also an important task. This paper gives a scenario of PMU measurements received to PDC (Phasor Data Concentrator) from PMUs placed in distinct locations and detection of transient events for post disturbance analysis. In this analysis, the disturbances are evaluated with the R programming analysis and compare findings of chronological data from separate locations and also shows the relation between disturbances in a grid. For this analysis, the impacts of frequency and voltage data are also considered.