On reliable and efficient smart grid

Abstract

Smart grid is the integration of renewable energy resources, and information and communication technologies into the electricity grid to achieve a reliable, costefficient, sustainable, and environment-friendly power grid. Nevertheless, the inherent intermittency of renewable energy resources poses serious challenges to the reliability of the power grid. In addition, smart grid requires a robust, reliable, efficient, and cost-effective communication network that meets its performance requirements. Finally, smart grid is a complex system that comprises components from both the power grid and communication networks. To understand the behavior of such a complex system, interactions and reciprocal effects between these components need to be fully investigated. There is, therefore, a need for research to: first, investigate the impact of massive integration of distributed energy resources to the grid and develop control mechanisms to mitigate their intermittency; second, to evaluate the performance of communication network protocols consistently with smart grid requirements; and finally to develop system-level modeling and simulation tools to study the interaction between the power grid and the communication network, and the effectiveness of smart grid applications. This dissertation aims to address these challenges through a comprehensive simulation-driven study of the smart grid. For the integration of renewable energy resources, we designed scenarios for different integration schemes, and propose a control mechanism to mitigate their variability. Through simulation experiments/ studies, we conducted a performance evaluation of these scenarios and validate the effectiveness of our control mechanism. For the communication network, we designed a network model and scenarios based on smart grid use cases. We then systematically compared the effectiveness of two representative wireless mesh network protocols- HWMP and AODV Protocols, and investigated the performance of WIMAX technology in smart grid communication networks with different modulation techniques. Finally, we designed a framework to explore co-simulation scenarios. Using the demand response and energy price as examples of smart grid applications and operating the communication network under various conditions, we implemented these scenarios and conducted a performance evaluation of smart grid applications by leveraging a co-simulation platform.