计及能量共享的5G基站电能实时调度优化策略

doi:10.19665/j.issn1001-2400.20230101

西安电子科技大学学报 ›› 2023, Vol. 50 ›› Issue (5): 44-53.doi: 10.19665/j.issn1001-2400.20230101

• 信息与通信工程 & 计算机科学与技术 • 上一篇下一篇

计及能量共享的5G基站电能实时调度优化策略

刘迪迪¹(),杨玉荟¹(),肖佳文¹(),杨益菲¹(),程鹏鹏¹(),张泉景²()

1.广西师范大学电子与信息工程学院,广西桂林 541004
2.西华师范大学教育信息技术中心,四川南充 637001

收稿日期:2022-08-29 出版日期:2023-10-20 发布日期:2023-11-21
通讯作者: 张泉景
作者简介:刘迪迪(1980—),女,副教授,E-mail:ldd866@gxnu.edu.cn;|杨玉荟(1997—),女,广西师范大学硕士研究生,E-mail:huiyuhui616@163.com;|肖佳文(1996—),男,广西师范大学硕士研究生,E-mail:1378301286@qq.com;|杨益菲(1998—),女,广西师范大学硕士研究生,E-mail:yangyifei031125@163.com;|程鹏鹏(1997—),男,广西师范大学硕士研究生,E-mail:1096087714@qq.com
基金资助:
国家自然科学基金(62061006);广西自动检测技术与仪器重点实验室基金(YQ23203);南充市社科规划项目(NC23C280);青年教师科研资助项目(23kq004)

Real-time power scheduling optimization strategy for 5G base stations considering energy sharing

LIU Didi¹(),YANG Yuhui¹(),XIAO Jiawen¹(),YANG Yifei¹(),CHENG Pengpeng¹(),ZHANG Quanjing²()

1. College of Electronic and information Engineering,Guangxi Normal University,Guilin 541004,China
2. College of Education and Information Technology Center,China West Normal University,Nanchong 637001,China

Received:2022-08-29 Online:2023-10-20 Published:2023-11-21
Contact: Quanjing ZHANG

摘要/Abstract

摘要：

为缓解第5代移动通信基站的巨大能耗导致的电网供电压力,联合分布式可再生能源、能量共享与能量存储提出了一个以最小化网络运营商的长期购电成本为目标的调度优化模型。综合考虑在可再生能源出力、各基站能量需求以及智能电网中的时变电价等先验统计信息均为未知的情况下,基于李雅普诺夫(Lyapunov)优化理论提出了一种低复杂度的第5代移动通信(5G)基站能量共享实时调度算法。在优化问题求解中将基站的柔性电能需求构造虚拟队列,并将基站储能时间耦合约束转化为虚拟队列稳定性问题,所提算法通过实时调度基站的产能、储能、用能和基站间的能量共享,在满足各基站用电需求的前提下,最小化网络运营商从外部电网购电的长期成本。理论分析表明,所提算法只需要根据当前系统状态进行实时决策,且优化结果能无限渐近最优值。仿真结果表明,所提出的算法可以有效地减少网络运营商的购电成本,相比基准贪婪算法1,购电成本可降低约43.1%。

关键词: 能量共享, 5G基站, 时变电价, Lyapunov优化, 能量存储, 实时算法

Abstract:

To alleviate the pressure on society's power supply caused by the huge energy consumption of the 5th generation mobile communication (5G) base stations,a joint distributed renewables,energy sharing and energy storage model is proposed with the objective of minimizing the long-term power purchase cost for network operators.A low-complexity real-time scheduling algorithm for energy sharing based on the Lyapunov optimization theory is proposed,taking into account the fact that the a priori statistical information on renewable energy output,energy demand and time-varying tariffs in smart grids are unknown.A virtual queue is constructed for the flexible electricity demand of the base stations in optimization problem solving.The energy storage time coupling constraint is transformed in the energy scheduling problem into a virtual queue stability problem.The proposed algorithm schedules the renewable energy output,energy storage,energy use and energy sharing of the base stations in real time,and minimizes the long-term cost of network operators purchasing power from the external grid on the premise of meeting the electricity demand of each base station.Theoretical analysis shows that all the proposed algorithm needs is to make real-time decisions based on the current system state and that the optimization result is infinitely close to the optimal value.Finally,simulation results show that the proposed algorithm can effectively reduce the power purchase cost of the network operator by 43.1% compared to the baseline greedy Algorithm One.

Key words: energy sharing, 5G base station, time-varying price, Lyapunov optimization, energy storage, real-time algorithm

中图分类号:

TN92

刘迪迪,杨玉荟,肖佳文,杨益菲,程鹏鹏,张泉景. 计及能量共享的5G基站电能实时调度优化策略[J]. 西安电子科技大学学报, 2023, 50(5): 44-53.

LIU Didi,YANG Yuhui,XIAO Jiawen,YANG Yifei,CHENG Pengpeng,ZHANG Quanjing. Real-time power scheduling optimization strategy for 5G base stations considering energy sharing[J]. Journal of Xidian University, 2023, 50(5): 44-53.

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参考文献 16

[1]	HUI H, DING Y, SHI Q, et al. 5G Network-Based Internet of Things for Demand Response in Smart Grid:A Survey on Application Potential[J]. Applied Energy, 2020, 257:1-13.
[2]	PILZ M, ISRAR A, YANG Q, et al. Renewable Energy Powered Sustainable 5G Network Infrastructure:Opportunities,Challenges and Perspectives[J]. Journal of Network and Computer Applications, 2021, 175:102910. doi: 10.1016/j.jnca.2020.102910
[3]	佚名. 《5G网络安全标准化白皮书》发布[J]. 信息网络安全, 2021, 6:98.
	YI Ming. 《White Paper on 5G Cybersecurity Standardization》 Publish[J]. Information Network Security, 2021, 6:98-98.
[4]	LI B, DAI Y H, DONGZ, et al. Energy-Efficient Resources Allocation with Millimeter-Wave Massive MIMO in Ultra Dense HetNets by SWIPT and CoMP[J]. IEEE Transactions on Wireless Communications, 2021, 20(7):4435-4451. doi: 10.1109/TWC.2021.3058776
[5]	宁晓晗, 雷维嘉. 能量收集多天线发送机的功率控制和天线选择[J]. 西安电子科技大学学报, 2022, 49(3):83-92.
	NING Xiaohan, LEI Weijia, Power Control and Antenna Selection for Themulti-Antenna Transmitter with Energy Harvesting[J]. Journal of Xidian University, 2022, 49(3):83-92.
[6]	张曦, 刘友波, 吕林, 等. 计及高压配电网负荷转供的城市220 kV片区电网供电能力分析[J]. 电网技术, 2017, 41(5):1612-1620.
	ZHANG Xi, LIU Youbo, LU Lin, et al. Analysis of the Power Supply Capacity of an Urban 220 kV Area Grid Considering Load Transfer from the High Voltage Distribution Network[J]. Power Grid Technology, 2017, 41(5):1612-1620.
[7]	刘迪迪, 孙浩天, 肖佳文, 等. 智能电网中终端用户的双向能量交易算法[J]. 西安电子科技大学学报, 2021, 48(3):131-137.
	LIU Didi, SUN Haotian, XIAO Jiawen, et al. Two-Way Energy Trading Algorithms for End-User in the Smart Grid[J]. Journal of Xidian University, 2021, 48(3):131-137.
[8]	HNANG G, ZHANG B, YAO Z, et al. Quality-Aware Video Streaming for Green Cellular Networks with Hybrid Energy Sources[J]. IEEE Internet of Things Journal, 2021, 8(10):8543-8556. doi: 10.1109/JIOT.2020.3046543
[9]	HAN T, ANAARI N. On Optimizing Green Energy Utilization for Cellular Networks with Hybrid Energy Supplies[J]. IEEE Transactions on Wireless Communications, 2013, 12(8):3872-3882. doi: 10.1109/TCOMM.2013.051313.121249
[10]	LENG B, GUO X, ZHENG X, et al. A Wait-and-See Two-Threshold Optimal Sleeping Policy for a Single Server with Bursty Traffic[J]. IEEE Transactions on Green Communications and Networking, 2017, 1(4):528-540. doi: 10.1109/TGCN.2017.2739825
[11]	FAROOQ M J, GHAZZAI H, KADRI A, et al. A Hybrid Energy Sharing Framework for Green Cellular Networks[J]. IEEE Transactions on Communications, 2017, 65(2):918-934. doi: 10.1109/TCOMM.2016.2637917
[12]	LEE H, LEE W. Adaptive Traffic Management and Energy Cooperation in Renewable-Energy-Powered Cellular Networks[J]. IEEE Systems Journal, 2020, 14(1):132-143. doi: 10.1109/JSYST.4267003
[13]	SHEN M,DHAI. D S, WANG X J et al. Intelligent Energy and Traffic Coordination for Green Cellular Networks with Hybrid Energy Supply[J]. IEEE Transactions on Vehicular Technology, 2017, 66(2):1631-1646. doi: 10.1109/TVT.2016.2554618
[14]	YIN F, ZENG M, ZHANG Z, et al. Coded Caching for Smart Grid Enabled HetNets with Resource Allocation and Energy Cooperation[J]. IEEE Transactions on Vehicular Technology, 2020, 69(10):12058-12071. doi: 10.1109/TVT.25
[15]	ALQASIR A M, KAMAL A. Cooperative Small Cell HetNets with Dynamic Sleeping and Energy Harvesting[J]. IEEE Transactions on Green Communications and Networking, 2020, 4(3):774-782. doi: 10.1109/TGCN
[16]	NEELY M J. Stochastic Network Optimization with Application to Communication and Queueing Systems[M]. Morgan & Claypool, 2010:20-105.

参数	数值	参数	数值
时间间隔/min	1	能量收集	泊松过程
时隙个数	43 200	能量需求	正态分布
储能设备容量/kJ	2 000	η_ch,η_dis	0.9,1.0/0.9
能量传递效率因子	0.95	C_i,_max,D_i,_max/kJ	200,200
e_i,_max/kJ	300	G_i,_max/kJ	1 000
V	830	电价范围/元	0.5~2.0

计及能量共享的5G基站电能实时调度优化策略

Real-time power scheduling optimization strategy for 5G base stations considering energy sharing

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