信息通信技术与政策

信息通信技术与政策

信息通信技术与政策 ›› 2025, Vol. 51 ›› Issue (5): 28-34.doi: 10.12267/j.issn.2096-5931.2025.05.004

专题:绿色低碳 上一篇    下一篇

基于运营商位置能力的充电桩规划与绿色能源协同研究

Charging stations planning and green energy coordination leveraging mobile operator location capabilities

张恩皖, 乔驰, 夏姚敏   

  1. 中国移动通信集团安徽有限公司,合肥 230088
  • 收稿日期:2025-03-21 出版日期:2025-05-25 发布日期:2025-06-18
  • 作者简介:
    张恩皖, 中国移动通信集团安徽有限公司研究员,长期从事大数据分析、建模挖掘、信息安全、量子通信等方面的研究工作
    乔驰, 中国移动通信集团安徽有限公司淮北分公司总经理,长期从事信息通信业与科技产业融合发展相关工作,基础通信网络、车联网/物联网、算力网络、人工智能、低空经济等相关应用领域专家。
    夏姚敏, 中国移动通信集团安徽有限公司人工智能专家,长期从事大数据建模、数据挖掘等方面的研究工作

ZHANG Enwan, QIAO Chi, XIA Yaomin   

  1. China Mobile Group Anhui Company Limited (China Mobile Group Anhui Co., Ltd.), Hefei 230088, China
  • Received:2025-03-21 Online:2025-05-25 Published:2025-06-18

摘要:

提出了一种基于运营商位置能力的新能源汽车充电需求预测模型,并设计了面向可再生能源的动态匹配策略。通过融合运营商位置数据、可再生能源发电数据和充电基础设施数据,构建了能够准确预测区域充电需求的长短期记忆网络模型。试验结果表明,该模型在预测精度上优于传统方法。同时,动态匹配策略能够有效提高可再生能源的本地消纳比例,并在一定程度上优化用户充电等待时间,为更精细化的充电基础设施规划和运营提供了新思路,并为促进清洁能源在交通领域的应用提供了技术支撑。

关键词: 充电桩, 充电需求预测, 运营商位置数据, 可再生能源集成, 动态匹配策略

Abstract:

This paper proposes an electric vehicle charging demand prediction model based on mobile operator location intelligence, and designs a dynamic matching strategy oriented toward renewable energy. By integrating operator location data, renewable energy generation data, and charging stations data, this paper constructs a long short-term memory network model that can accurately predict regional charging demands. The test results show that this model significantly outperforms traditional methods in prediction accuracy. And the dynamic matching strategy effectively increases the local consumption ratio of renewable energy and optimizes users' charging waiting time to a certain extent. This research provides new insights for refined planning and operation of charging stations, and offers technical support for promoting clean energy applications in the transportation field.

Key words: charging stations, charging demand prediction, operator location data, renewable energy integration, dynamic matching strategy

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