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Open Access Publications from the University of California

DISTIL: Design and Implementation of a Scalable Synchrophasor Data Processing System.


The introduction and deployment of cheap, high precision, high-sample-rate next-generation synchrophasors en-masse in both the transmission and distribution tier – while invaluable for event diagnosis, situational awareness and capacity planning – poses a problem for existing methods of phasor data analysis and storage.

Addressing this, we present the design andimplementation of a novel architecture for synchrophasor data analysis on distributed commodity hardware. At the core is a newfeature-rich timeseries store, BTrDB.

Capable of sustained writes and reads in excess of 16 million points per second per cluster node, advanced query functionality and highly efficient storage, this database enables novel analysis and visualization techniques.

Leveraging this, a distillate framework has been developed that enables agile development of scalable analysis pipelines with strict guarantees on result integrity despite asynchronous changes in data or out of order arrival. Finally, the system is evaluated in a pilot deployment, archiving more than 216 billion raw datapoints and 515 billion derived datapoints from 13 devices in just 3.9TB.

We show that the system is capable of scaling to handle complex analytics and storage for tens of thousands of next-generation synchrophasors on off-the-shelf servers.

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