Charging Facility Monitoring Stream Analysis based on Hadoop for Smart Grids

Charging facilities, which are being constructed for the wide penetration of electric vehicles, keep generating a massive amount of real-time status readings. The analysis of those streams provides a useful guideline for power provisioning and facility management. This paper first develops a charging facility monitoring system mainly interfacing chargers and the total operation system. Then, it builds a Hadoop-based framework which converts the raw data stream into manageable forms, filters information fields of interest, and creates preliminary statistics for the next-step analysis. Upon the set of records stored in the Linux file system, Pig scripts are implemented to obtain the number of reports as well as the amount of energy supplied to vehicles for each charger, vehicle, day, and time-of-day. The experiment finds a significant difference between respective electric vehicle entities resulting from the personal ownership and vehicle locations, making it possible to systematically integrate and analyze the future complex charger streams.

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