混合供能蜂窝网络的投资回报率和碳效联合优化

Joint optimization of return on investment and carbon efficiency for greencellular networks with hybrid energy supply

为解决“5G基站+光伏+储能”系统难以兼顾系统经济性与蜂窝网络性能的问题,提出双层优化模型。外层模型将时间尺度压缩在1天,采用基于模拟退火的粒子群算法求解基站光伏储能容量,其优化目标为在满足光伏利用率要求下,使得系统投资回报率最大。内层模型将时间尺度确定在1小时,采用拉格朗日对偶分解方法求解基站发射功率分配策略,其优化目标为在满足用户服务速率要求下,使得网络逐小时碳排放效率最优。通过对混合供能蜂窝网络系统经济性分析,分别得出了系统投资回报率、碳效与系统光伏板面积、电池储能容量的关系。仿真结果表明,使用提出的算法可使得系统投资回报率达到380.3%,光伏利用率达到96.5%;其内层碳效优化算法相较于注水算法碳排放量降低了31.8%。

In order to solve the problem that“5G base station+photovoltaic system+battery energy storage system”system is difficult to balance the system economy and cellular network performance,in this paper,a two-layer optimization model is established to solve this joint optimization problem.In the outer model,the time scale is compressed to 1 day,and the simulated annealing-particle swarm optimization algorithm is used to solve the photovoltaic energy storage capacity of the base station configuration.The optimization goal is to maximize the return on investment of the system while meeting the requirements of utilization of photovoltaic energy.In the inner model,the time scale is set at 1 hour,and the Lagrange duality decomposition method is used to solve the transmission power distribution strategy of the base stations.The optimization goal is to make the hourly carbon efficiency of the network optimal under the requirement of user service rate.Through the economic analysis of the hybrid energy supply cellular network system,the relationship between return on investment of system and the photovoltaic area and battery energy storage capacity of system is obtained,respectively,and so is carbon efficiency.Simulation results show that return on investment of the system can reach 380.3%and the utilization of photovoltaic energy can reach 96.5%by using the algorithm in this paper.Compared with the water filling algorithm,the inner carbon efficiency optimization algorithm reduces carbon emissions by 31.8%.