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Processed PMU data used in Black Box Attack on Machine Learning Assisted
Wide Area Monitoring and Protection Systems
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Reference Paper :
M. Biswal, S. Misra and A. S. Tayeen, "Black Box Attack on Machine Learning Assisted Wide Area Monitoring and Protection Systems," 2020 IEEE Power & Energy Society Innovative Smart Grid Technologies Conference (ISGT), Washington, DC, USA, 2020, pp. 1-5, doi: 10.1109/ISGT45199.2020.9087762.
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This dataset contains images that represent PMU data described in the reference paper.
Each image has a dimension of [300X20X3] comprising of 300 time points, 10 voltage and 10 frequency measurements, and 3 fundamental
color intensities. Each of the image represents the instance of a disturbance. We consider a disturbance pattern length of 5s, with 0:5s before the trigger and 4:5s after the trigger. Voltage and frequency data streams from 10 PMUs at a sampling rate of 60 frames per second, were aggregated to form these pseudo color images. 

The data-set consisted of :
1. 344 instances of faults located in the sub-folder “DB_FLT”
2. 140 instances of loss of generation located in the sub-folder “DB_GNL”
3. 21 instances of synchronous motor switching events  located in the sub-folder “DB_SMS”.

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