绿电交易背景下5G基站降碳路径分析

doi:10.12204/j.issn.1000-7229.2023.06.006

电力建设 ›› 2023, Vol. 44 ›› Issue (6): 53-60.doi: 10.12204/j.issn.1000-7229.2023.06.006

• 支撑碳达峰、碳中和的能源电力技术、经济和政策·栏目主持赵俊华副教授、邱靖博士、文福拴教授· • 上一篇下一篇

绿电交易背景下5G基站降碳路径分析

吴建斌¹^,³(), 任中睿²(), 薛磊¹(), 李强¹(), 高玮¹(), 谭忠富²()

1.国网山西省电力公司经济技术研究院,太原市 030000
2.华北电力大学经济与管理学院,北京市 102206
3.国网山西省电力公司,太原市 030021

收稿日期:2022-06-30 出版日期:2023-06-01 发布日期:2023-05-25
作者简介:吴建斌(1971),男,高级工程师,主要研究方向为低碳经济、电网规划,E-mail:1016662936@qq.com;
任中睿(1994),男,博士研究生,主要研究方向为能源低碳转型,E-mail:renzhongrui1994@163.com;
薛磊(1980),男,高级工程师,主要研究方向为能源经济,E-mail:hulate@126.com;
李强(1977),男,高级工程师,主要研究方向为能源经济,E-mail:victorlq@163.com;
高玮(1987),女,工程师,主要研究方向为低碳经济,E-mail:gxmu07@163.com;
谭忠富(1964),男,博士,教授,主要研究方向为能源低碳转型、电力市场,E-mail:tanzhongfu@sina.com。
基金资助:
国网山西省电力公司科技项目“5G基站和电网资源共享研究”(52053320000A)

Carbon Reduction Path Analysis of 5G Base Stations in the Context of Green Power Trading

WU Jianbin¹^,³(), REN Zhongrui²(), XUE Lei¹(), LI Qiang¹(), GAO Wei¹(), TAN Zhongfu²()

1. State Grid Shanxi Economic and Technological Research Institute, Taiyuan 030000, China
2. School of Economic and Management, North China Electric Power University, Beijing 102206, China
3. State Grid Shanxi Electric Power Company, Taiyuan 030021, China

Received:2022-06-30 Online:2023-06-01 Published:2023-05-25
Supported by:
Science and Technology Project of State Grid Shanxi Electric Power Company(52053320000A)

摘要/Abstract

摘要：

5G的出现将推动社会变革,但5G网络需要建设大量基站,导致更大的碳排放,如何科学分析5G基站碳减排潜力,提出有效的降碳路线,是信息通信技术行业亟待解决的问题。首先,在绿电交易背景下,考虑基站规模、单站能耗、绿电比例、排放系数等因素,构建了基于Kaya恒等式的5G基站碳排放核算模型;在此基础上,利用对数平均迪氏分解法(log mean Divisia index,LMDI)建立了碳减排贡献度分析模型;最后,通过情景分析法对我国5G基站碳减排潜力与碳减排因素贡献度进行了分析。结果表明,对于碳增长,基站规模始终是最大的驱动因素;对于碳减排,基准情景与既定政策情景中单站能耗贡献最大,低碳政策情景中绿电交易比例贡献最大。因此,就5G基站降碳路径而言,参与通信基础设施共建共享以减少基站规模是根本途径,提升绿色节能技术以减少单站能耗是主要手段,扩大绿电交易规模以提高绿电交易比例是提前实现“双碳”目标的关键举措。研究结果和结论可为信通行业开展“双碳”工作提供借鉴。

关键词: 绿电交易, 5G基站, 碳减排, 对数平均迪氏(LMDI)分解

Abstract:

The emergence of 5G networks will drive social change. However, 5G networks require construction of numerous base stations, leading to greater carbon emissions. Scientifically analyzing the carbon reduction potential of 5G base stations and proposing an effective carbon reduction route are urgent issues for the information and communications technology (ICT) industry to address. First, in the context of green power trading, a 5G base station carbon emission accounting model based on the Kaya identity is constructed by considering factors such as base station scale, single-station energy consumption, green power ratio, and emission coefficient. A carbon emission reduction contribution analysis model is established using the logarithmic mean Divisia index (LMDI) decomposition method, and the carbon emission reduction potential and carbon emission reduction factor contribution of 5G base stations in China are analyzed using the scenario analysis method. The results show that, for carbon growth, the base station scale is always the greatest driver; for carbon reduction, single-station energy consumption contributes the most to the baseline and established policy scenarios, and the proportion of green power trading contributes the most to the low-carbon-policy scenario. Therefore, for the 5G base station carbon reduction path, participating in the common construction and sharing of communication infrastructure to reduce the base station size is a fundamental way to upgrade green energy-saving technologies to reduce single-station energy consumption. Expanding the scale of green power trading to increase the proportion of green power trading is the key initiative to achieve the target ahead of schedule. The findings and conclusions of this study can provide a reference for the ICT industry to conduct double-carbon work.

Key words: green power trading, 5G base stations, carbon reduction, logarithmic mean Divisia index(LMDI) decomposition

中图分类号:

TM-9

吴建斌, 任中睿, 薛磊, 李强, 高玮, 谭忠富. 绿电交易背景下5G基站降碳路径分析[J]. 电力建设, 2023, 44(6): 53-60.

WU Jianbin, REN Zhongrui, XUE Lei, LI Qiang, GAO Wei, TAN Zhongfu. Carbon Reduction Path Analysis of 5G Base Stations in the Context of Green Power Trading[J]. ELECTRIC POWER CONSTRUCTION, 2023, 44(6): 53-60.

图/表 7

图1 5G基站规模变化趋势

Fig.1 5G base station scale change trend

图2 4G基站规模变化趋势

Fig.2 4G base station scale change trend

图3 5G基站能耗分布占比

Fig.3 5G base station energy consumption distribution ratio

表1 情景参数变化率设置

Table 1 Scenario parameter change rate setting

图4 不同情景5G基站碳排放

Fig.4 Carbon emissions from 5G base stations for different scenarios

图5 不同情景碳排放因素贡献值

Fig.5 Contribution values of carbon emission factors for different scenarios

表2 不同情景碳排放因素贡献率

Table 2 Contribution rates of carbon emission factors for different scenarios

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绿电交易背景下5G基站降碳路径分析

Carbon Reduction Path Analysis of 5G Base Stations in the Context of Green Power Trading

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