Resilient hybrid overlay model for smart grid: RHM for smart grid

Abstract

In this paper, hybrid wireless sensor network model is envisaged over the power distribution grid for monitoring the health of the grid. The hybrid model is hierarchical. At the lower level, it uses a cluster topology at each tower to collect local information about the tower while at the higher level it uses linear chain topology to send the grid data to the base station (usually at the substation). Data is collected at each tower, aggregated over the linear chair network, and sent across to a base station for analysis. For analysis, a machine learning based model is employed. The model is designed to detect and classify anomalies in the sensory data and it ensures the security and stability of the smart grid. Initial topology model was investigated using a pilot simulation study followed by experimentation while the analysis is carried using the real time data collected using wireless sensor networks as an overlay network on the power distribution grid. Preliminary results show that detection mechanism is promising and is able to detect the occurrence of any anomalous event that may cause threat to the smart grid.