基于改进粒子群优化算法的智能电网频谱分配方法

Spectrum Allocation Method for Smart Grid Based on Improved Particle Swarm Optimization Algorithm

为满足用户日益增长的电力供应等方面的需求,提出了新型电网结构——智能电网。它可以有效提高能源安全以及电网的稳定性。然而,随着无线用户越来越多,频谱资源越来越匮乏,现有的固定频谱分配技术大大降低了频谱利用率。首先,建立基于认知无线电(CR)的智能电网频谱分配模型;然后,以系统平均收益(SAR)为目标函数,提出一种基于改进粒子群优化(PSO)的智能电网频谱分配方法。该方法解决了传统PSO算法容易陷入局部最优、收敛速度慢等问题。通过设计非线性变化加速因子来平衡全局搜索和局部开发能力,从而得到全局最优解。仿真结果表明,所提出的改进PSO算法收敛速度更快、搜索能力更强,能有效解决智能电网的频谱分配问题,最大化系统平均收益,从而提高频谱利用率。

In order to satisfy the growing demand for power supply,a new grid structure,namely the smart grid,had been proposed for effectively improving energy security and grid stability.However,with the increasing number of wireless users and the scarcity of spectrum resources,the existing fixed spectrum allocation techniques had greatly reduced the spectrum utilization.Therefore,a smart grid spectrum allocation model based on cognitive radio(CR)was first established.Then,taking system average revenue(SAR)as objective function,a spectrum allocation method based on improved particle swarm optimization(PSO)was proposed to solve the problems of easily falling into local optimum and slow convergence in the traditional PSO algorithm.Nonlinear acceleration factors were adopted to balance the universal search and local exploitation ability and consequently achieve the global optimal solution.Simulation results showed that the improved PSO has faster convergence speed and better search ability,which can effectively solve the problem of spectrum allocation of smart grid,maximize the average system revenue and thus improve the spectrum utilization.