认知智能电网邻域网络的频谱分配策略

doi:10.11896/jsjkx.190600027

Abstract

Abstract: Reliable and efficient communication network is the premise to give full play to the potential of smart grid.In view of the problems existing in the wireless communication environment of smart grid,such as the shortage of spectrum and low efficiency of resource utilization,this paper applied cognitive radio technology to the neighborhood network communication of smart grid.The concept of cognitive smart grid was introduced to ensure the fairness and effectiveness of service transmission.After considering the SNR and path loss in the communication process,the network throughput was selected as the channel benefit,and the modeling and simulation were carried out in urban residential areas with fixed topology.On this basis,an improved spectrum allocation algorithm for binary cat swarm (WBCSO) optimization was proposed.Firstly,the inertia weight of nonlinear dynamics is added into the speed update formula of binary cat swarm algorithm (BCSO),which decreases linearly with the increase of iteration times to prevent premature algorithm.Secondly,a breeding operator is introduced to generate offspring to increase the diversity of the population and obtain a better global optimal solution.Then,four common benchmark functions are selected to test the performance of the improved algorithm.The test results show that the optimized mean and standard deviation of WBCSO algorithm are better than that of BCSO algorithm.With the overall benefit of the system and the fairness of users as the optimization objectives,the proposed algorithm was compared with binary genetic algorithm (BGA) and binary particle swarm optimization (BPSO) on the contrast experiment.The simulation experiments show that WBCSO algorithm eventuallysystem total benefits and user fairness index of WBCSO algorithm is higher than BCSO algorithm with 13.7% and 14.6%respectively,and its performance is better than BPSO and BGA.Therefore,the improved binary cat swarm algorithm has the characteristics of fast convergence and strong search ability in the spectrum allocation of the neighborhood network of cognitive smart power grid.

Key words: Binary cat swarm algorithm, Cognitive smart grid, Inertial weight, Neighborhood network, Spectrum allocation

CLC Number:

TN939

WANG Yi-rou,ZHANG Da-min,XU Hang,SONG Ting-ting,FAN Ying. Spectrum Allocation Strategy for Neighborhood Network Based Cognitive Smart Grid[J].Computer Science, 2020, 47(3): 267-272.

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Spectrum Allocation Strategy for Neighborhood Network Based Cognitive Smart Grid

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