Adaptive rate stream processing for smart grid applications on clouds

Abstract

Pervasive smart meters that continuously measure power usage by consumers within a smart (power) grid are providing utilities and power systems researchers with unprecedented volumes of information through streams that need to be processed and analyzed in near realtime. We introduce the use of Cloud platforms to perform scalable, latency sensitive stream processing for eEngineering applications in the smart grid domain. One unique aspect of our work is the use of adaptive rate control to throttle the rate of generation of power events by smart meters, which meets accuracy requirements of smart grid applications while consuming 50% lesser bandwidth resources in the Cloud.