Design and simulation of a smart power grid communication network over TV white space using cognitive machine-to-machine networking

Abstract

Most of the current power grid networks are coupled with lots of inefficiencies mainly due to constant outages, overloading during peak times, service disruptions that are never reported in time and a lack of customer usage data and patterns in order to better understand and serve the customers. This is mainly due to lack of a reliable communication infrastructure between the grid devices, the provider and the customers. Scarcity of available spectrum, limited range of most unlicensed spectrum frequencies coupled with human inefficiencies are the biggest hindrances to building an effective communication network that can span the wide geographical regions covered by most grid networks. However, with the coming of age of cognitive radio technology that allows for spectrum sharing and allows opportunistic access to unused spectrum, spectrum utilization can be enhanced. The migration from analogue to digital television transmissions has freed large portions of the spectrum in the UHF/VHF bands that can be used for long distance propagation while the emergence of cognitive machine to machine communications can help eliminate human related inefficiencies resulting in timely production, exchange and processing of information. In this thesis, a smart grid communication network is designed utilizing dynamic spectrum access and TV white space using cognitive machine to machine networking. The designed smart grid communication network is able to acquire and process real time data from the grid hence allowing for automatic control and operation of the various systems in response to the users’ needs. This in turn allows the utility companies to effect dynamic pricing structures where they charge higher prices during peak times and lower prices during off-peak times. This can then be used as one of the mechanisms to achieve load balancing.