Cross Layer Optimized ZigBee-based Data Collection and Monitoring of Grid Systems

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Incorporating information and communication technologies into grid systems provides advanced capabilitiesfor remote, and real-time monitoring and control of devices. In smart grid systems, wireless relays are used inthe data collection for fault detection and power quality analysis. When wireless base stations are closer to highvoltage transmission lines, the signals from the base stations impact the monitoring of the lines as impulsivenoise. With the growing number of cellular base stations mainly in urban areas, this impulsive noise becomes aproblem causing the loss of data integrity when wirelessly transmitted. In this project, we will study thisproblem to quantify the loss of data and to determine the number of additional relays required to maintain thesame data quality in this noisy environment. This will help optimize the relay system operations (number ofrelays and locations) when excessive noise is detected in power lines.In particular, a hybrid network architecture comprised of wireless sensor networks and cellular network will beconsidered to monitor the high voltage transmission lines in the urban and suburban areas. Corona noise is oneof the sources of electromagnetic interference in such lines. We will first characterize the wireless channel withimpulsive Corona noise near cellular base stations; then formulate and solve the problem of finding theoptimum number of relays/sensors in a Zigbee-based linear and non-linear wireless sensor networks. Goal is todevelop a matrix with the expected number of additional relays and their locations needed to maintain the samedata quality for various intensity of noise level. The effects of physical and MAC layer parameters on themonitoring performance will also be quantified and included in the matrix to be used as operational guidelinesin the relay system.