Demand Response Management Research Based on Cognitive Radio for Smart Grid

Abstract

Cognitive radio is introduced into the demand response management (DRM) of smart grid with the hope of alleviating the shortage of spectrum resources and improving communication quality. In this paper, we adopt an energy detection algorithm based on generalized stochastic resonance (GSRED) to improve the spectrum sensing accuracy under the circumstances of low signal-to-noise ratio without increasing system overhead. Specifically, a DRM scheme based on real-time pricing is investigated, and the social welfare is taken as the main index to measure system control performance. Furthermore, considering the adverse effects incurred by incorrect spectrum sensing, we incorporate the probability of the DRM system causing interference to primary user and spectrum loss rate into the evaluation index of the system control performance and give the final expression of the global optimization problem. The influence of sensing time on system communication outage probability and spectrum loss rate is elaborated in detail through theoretical derivation and simulation analysis. Simulation results show that the GSRED algorithm has higher detection probability under the same conditions compared with the traditional energy detection algorithm, thus guaranteeing lower communication outage probability and spectrum loss rate.