Spectrum Sensing for Demand Response Management in Smart Grid

Demand response management (DRM) is considered to play a key role in the implementation of smart grid, which requires reliable and real-time communication between power suppliers and consumers. Cognitive radio technology is introduced into smart grid to alleviate the shortage of spectrum resources and improve communication quality. To ensure the performance of spectrum sensing under low signal-to-noise ratio, we adopt an energy detection algorithm based on generalized stochastic resonance (GSRED) algorithm to achieve reliable spectrum sensing without significantly increasing the complexity and sensing delay of the DRM system. In this paper, we investigate a DRM method based on real-time pricing, and give the expression of the global optimization problem. At the same time, we analyze the influence of the outage probability and sensing time on the control performance of DRM, and give the corresponding simulation results. The simulation results show that the GSRED algorithm is significantly better than the traditional energy detection algorithm to ensure lower outage probability and better control performance. Furthermore, setting a reasonable sensing time can maximize the social welfare of the smart grid and optimize the DRM control performance without excessively increasing the system delay and overhead.