College of Big Data and Information Engineering of GuizhouUniversity，
the Natural Science Foundation of Guizhou Province, China (Grant No. 1047)
In view of the problems such as spectrum shortage and low utilization efficiency of wireless communication environment of smart grid, this paper applies cognitive radio technology to the neighborhood network communication of smart grid. The concept of cognitive smart grid is introduced to ensure the fairness and effectiveness of business transmission, and a spectrum allocation strategy based on the improved binary Butterfly Optimization Algorithm (BOA) is proposed, which takes into account the signal-to-noise ratio and path loss in the communication process, and selects the system energy efficiency as the channel benefit. The modeling and simulation are carried out in urban residential areas with fixed topology. Firstly, spectrum are allocated for cognitive smart grid users with the Binary Butterfly Optimization Algorithm based on Improved time-varying conversion function and disturbance strategy(IBBOA), and then the transmission power of the user is dynamically adjusted by the closed-loop power control algorithm based on the received signal-to-noise ratio, which reduces the interference between the cognitive smart grid users and the main users. Finally, with the system energy efficiency and two fairness indexes of users as the optimization objectives, Genetic Algorithm (GA) and the Binary Particle Swarm Optimization (BPSO) has carried on the contrast, and the simulation experiment shows that the IBBOA algorithm joint closed-loop power control obtained 33.2% higher system energy efficiency than the NBOA algorithm without joint closed-loop power control, and the final system energy efficiency and the user fairness index Fair of the IBBOA algorithm were 47.8% and 62.6% higher than the worst-performing GA algorithm respectively. Compared with the previous BBOA algorithm, which was 17.6% and 26.7% higher respectively. And it"s also that the scheme can effectively suppress the interference between users in the cognitive smart grid, and greatly improve the spectrum utilization and system energy efficiency.