Cognitive Radio Based Smart Grid Communication System

Abstract

Smart grid (SG) concepts have revolutionized the future of conventional electric grid by making it more efficient, resilient and reliable using state-of-the-art technologies, modern equipment, and automation control systems. However, the full realization of all the above-mentioned benefits is not possible without the implementation of a fast, reliable and economical communication network that must exhibit spectral and energy efficiency. Additionally, the data generated by various SG applications is not only in enormous proportion but also diverse in nature in terms of its delay tolerance. The crucial need to transmit a significant amount of smart grid applications data in a spectral efficient manner makes cognitive radio (CR) technology most suitable for SG environment. Identically, TV white spaces (TVWS) is the most expectant candidate for CR based smart grid communication network (CRSGCN). Using CR in SGCN will bring its own set of communication problems. There is not much of a research available for problems associated with CRSGCN and primarily, this is the motivation behind this research work. This dissertation addresses some critical challenges in the design of CRSGCN. The research work can be divided into two parts. First, we present a comprehensive survey to establish the diverse communication requirements for three subsets of SGCN: Home Area Network (HAN), Neighborhood Area Network (NAN) and Wide Area Network (WAN). Then, we review SG applications to analyze what kind of data is suitable to be carried over CR technology. Based on these requirements, we propose a CR based end-to-end network architecture for SGCN by using IEEE communication standards suitable for delay-tolerant data such as required by automatic metering infrastructure (AMI) and demand response (DR) etc. Then, we identify salient features of the proposed network architecture that makes it a viable solution along with some open issues and challenges, related to CRSGCN. The second part is then dedicated to address resource allocation in CRSGCN, in particular, the two most important researched areas related to CR, i.e., channel allocation (CA) and power allocation (PA). We modeled a communication scenario based on CRSGCN architecture proposed in part one, by dividing the service area into groups of secondary users (SUs) called NAN clusters, depending upon the distance of Smart Meters (SMs) from Data Concentrator Unit (DCU). Then, we formulated a multiple constraint NP-hard CA problem using interference avoidance strategy by considering two practical scenarios: fairness-based allocation and priority-based allocation. We then propose our CA algorithm based on Cat Swarm Optimization (CSO) to eliminate the severe integer constraints of the problem under consideration. Next, for the same NAN communication scenario using IEEE 802.11af standard via open loop regulatory framework for TVWS, we formulate a joint power and channel allocation (JPCA) problem. Next, we present an efficient PA scheme, meeting quality-of-service (QoS) requirements, followed by CA scheme based on cuckoo search algorithm (CSA). The performance of the proposed solutions is analyzed using exhaustive simulations to optimize power consumption, fairness and user rewards. The presented results in the form of graphs and numerical comparisons indicate the effectiveness of our allocation algorithm to achieve the desired objectives. We have investigated and formulated a JPCA problem with multiple constraints considering two practical cases of fairness-based allocation and priority-based allocation in an SG environment in an innovative way, which perhaps is among pioneer and premiere works in its technical domain. We hope, this work will be regarded as a corner stone in CRSGCN and will pave way for more future studies in this domain.