湖北民族大学学报（自然科学版）2025，Vol.43Issue(2)：237-243,265,8.DOI:10.13501/j.cnki.42-1908/n.2025.06.011
基于改进白鲸算法的5G基站微电网双层容量优化
Dual-layer Capacity Optimization for 5G Base Stations Microgrids Based on Improved Beluga Whale Algorithm
摘要
Abstract
To alleviate the pressure of energy consumption and fully exploit the scheduling potential of the system,a dual-layer capacity optimization model for the″planning-operation″of a 5th generation mobile network(5G)base station microgrid based on renewable energy generation as well as a fast solving algorithm was proposed.On the planning layer,the model aimed to minimize the total life-cycle cost,while in the scheduling layer,it focused on minimizing the operational cost.The iterative optimization of the dual-layer model provided the optimal solution for capacity allocation and operational scheduling.Furthermore,the improved beluga whale optimization(IBWO)algorithm incorporated the inverse elite strategy,vertical-horizontal crossover strategy,and whirlwind foraging strategy to enhance global search capability and accelerate convergence.Finally,the energy consumption characteristics of 5G base stations were thoroughly analyzed,and a power aggregation model was constructed by distinguishing between sensitive loads requiring immediate processing and tolerant loads that could be delayed.Standby energy storage was scheduled to enhance regulatory flexibility.The results demonstrated that,compared to particle swarm optimization,grey wolf optimization,and traditional beluga whale optimization algorithms,the IBWO algorithm reduced daily operational costs by 26.20%,20.54%,and 20.30%,respectively,and annual comprehensive costs by 15.39%,12.87%,and 10.84%,respectively.This study played an important role in reducing the comprehensive cost of 5G base stations and improving the system scheduling capability.关键词
5G基站/容量优化/储能调控/双层模型/改进白鲸算法Key words
5G base stations/capacity optimization/energy storage regulation/dual-layer model/improved beluga whale algorithm分类
信息技术与安全科学引用本文复制引用
幸巧巧,李时东,廖钦一,李云翔..基于改进白鲸算法的5G基站微电网双层容量优化[J].湖北民族大学学报（自然科学版）,2025,43(2):237-243,265,8.基金项目
国家自然科学基金项目(62365009) （62365009）
湖北省教育厅中青年团队项目(T2021013). （T2021013）
