Multi-time-scale Optimization Method for 5G Base Station Considering Backup Energy Storage and Air-conditioning Scheduling Potential

QIAO Ruixun; WANG Junhua; WEI Daoming; CAI Changsong; SHAO Jianwei; LIU Shiqi

doi:10.7500/AEPS20220527005

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Multi-time-scale Optimization Method for 5G Base Station Considering Backup Energy Storage and Air-conditioning Scheduling Potential

Application Research | 更新时间：2025-06-16

- Multi-time-scale Optimization Method for 5G Base Station Considering Backup Energy Storage and Air-conditioning Scheduling Potential
- Automation of Electric Power Systems Vol. 47, Issue 4, Pages: 111-120(2023)
- 作者机构：
  
  武汉大学电气与自动化学院，湖北省武汉市 430072
- 作者简介：
- 基金信息：
  
  Postdoctoral Science Foundation of China(2021TQ0249);National Key R&D Program of China(2017YFB1201002)
- DOI：10.7500/AEPS20220527005
  CLC：
- Received：27 May 2022，
  
  Revised：2022-08-27，
  
  Published Online：14 December 2022，
  
  Published：25 February 2023
- 稿件说明：
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乔锐勋,王军华,韦道明等.计及后备储能及空调调度潜力的5G基站多时间尺度优化方法[J].电力系统自动化,2023,47(4):111-120.

QIAO Ruixun,WANG Junhua,WEI Daoming,et al.Multi-time-scale Optimization Method for 5G Base Station Considering Backup Energy Storage and Air-conditioning Scheduling Potential[J].Automation of Electric Power Systems,2023,47(4):111-120.
乔锐勋,王军华,韦道明等.计及后备储能及空调调度潜力的5G基站多时间尺度优化方法[J].电力系统自动化,2023,47(4):111-120. DOI： 10.7500/AEPS20220527005.

QIAO Ruixun,WANG Junhua,WEI Daoming,et al.Multi-time-scale Optimization Method for 5G Base Station Considering Backup Energy Storage and Air-conditioning Scheduling Potential[J].Automation of Electric Power Systems,2023,47(4):111-120. DOI： 10.7500/AEPS20220527005.

摘要

含可再生能源(RES)的第五代移动通信(5G)基站的广泛接入有利于推动通信设施的低碳化发展，然而RES及通信负荷的不确定性给5G基站及电网的安全运行带来了挑战。基于此，提出一种计及后备储能及空调负荷调度潜力的5G基站多时间尺度滚动优化调度模型，在日前阶段以基站综合运行成本最低为目标函数；在日内阶段以日前计划为基础，通过调整后备储能及变频空调的出力来最小化功率偏差惩罚成本及温度偏差成本。然后，采用基于可忽略修复时间马尔可夫模型的基站后备储能可调度容量评估方法，将其作为储能模型边界约束集成到优化模型中，提高了基站供电的可靠性。算例仿真结果表明，采用所提出的模型能够使得基站运行成本相较日前值下降2.98%，联络线功率波动率仅为3.19%，在提升基站运行经济效益的同时又能有效降低源荷波动性对系统实际运行的影响。

Abstract

The widespread access of the 5th generation mobile communication (5G) base stations containing renewable energy source (RES) is conducive to promoting the low-carbon development of communication facilities. However

the uncertainty of RES and communication load brings challenges to the safe operation of 5G base stations and power grids. Based on the above issues

this paper proposes a multi-time-scale rolling optimization scheduling model for 5G base stations considering the backup energy storage and air-conditioning scheduling potential

with the lowest comprehensive operation cost of base stations as the objective function in the day-ahead phase. The intraday phase is based on the day-ahead plan

and minimizes the penalty cost of power deviation and the cost of temperature deviation by adjusting the output of backup energy storage and inverter air-conditioner. Then

a method based on Markov repairable system with repair time omission is adopted to evaluate the dispatchable capacity of the backup energy storage

which is integrated into the optimization model as the boundary constraint of the energy storage model to improve the reliability of the base station power supply. The simulation results show that the proposed model can reduce the base station operation cost by 2.98% compared with the day-ahead value

and the tie-line power fluctuation rate is only 3.19%

which can improve the operation economic efficiency of base stations while effectively reducing the influence of source-load fluctuation on the actual operation of the system.

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