Distributed Architecture for Managing Big Data in Smart Grid

A Thesis Submitted to the Faculty of Graduate Studies and Research In Partial Fulfillment of the Requirements for the Degree of Master of Engineering in Electronic Systems Engineering, University of Regina. xi, 84 p. Smart grid is a technological advancement to the traditional power system that provides efficient and reliable utilization of energy resources. Large number of sensors are becoming part of the power network to improve its efficiency. These sensors enable communication between home appliances and power generators to enhance home appliance automation, monitoring and remote control capabilities. As smart power grid incorporates a large number of data-generating embedded sensors; key questions are where in the network to process and analyze the data, and how to perform the analysis. The data in smart grid can be processed either by one central processor or through multiple distributed processors. This thesis proposes a smart grid distributed architecture involving home sensors talking to a smart gateway in the home for local processing, which then passes processed data to a central processor for further analysis. As part of our work, a test bed is designed to highlight advantages of distributed smart grid architecture by comparing central and local processing of data. An open data set is used to feed power sensor data into the test setup. This thesis discusses variety of operations that can be performed in the distributed architecture of smart grid. It is shown that the local processing of data can improve efficiency by effectively utilizing available network bandwidth. Furthermore, local processing is favorable for smart grid applications that are time critical as local processing has less delay and jitters for data communication round trip time as compared to central processing. Moreover, we discuss that certain calculations like energy usage prediction for home appliances can effectively be done locally while central processor can be used for coordination between different local processors. Student yes