| 引用本文: | 程子霞,万佳源,柴旭峥.基于分层聚合的5G基站虚拟电厂互动能力评估及优化研究[J].电力系统保护与控制,2026,54(07):140-151. |
| CHENG Zixia,WAN Jiayuan,CHAI Xuzheng.Evaluation and optimization of interaction capability of 5G base station virtual power plants based on hierarchical aggregation[J].Power System Protection and Control,2026,54(07):140-151 |
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| 摘要: |
| 针对5G基站虚拟电厂(virtual power plant, VPP)参与电网互动过程中通信业务约束与电力调控难以协同、调节能力量化精度不足等问题，提出一种基于分层聚合的5G基站VPP互动能力评估与优化方法。首先，结合5G基站的运行特性，构建“单基站层-基站集群层-VPP多元能源聚合层”的分层聚合模型，明确不同层级下调节能力的评估指标与计算流程。然后，在满足通信服务质量(quality of service, QoS)约束的前提下，建立计及基站储能的优化调度模型，并引入灰狼优化算法(grey wolf optimizer, GWO)实现多约束条件下的协同优化求解。最后，通过仿真分析对所提方法进行验证。结果表明，该方法能够有效提升5G基站虚拟电厂的调节灵活性与运行经济性，为通信-电力协同运行提供技术支撑。 |
| 关键词: 5G基站 虚拟电厂 分层聚合 灰狼优化算法 |
| DOI：10.19783/j.cnki.pspc.250862 |
| 分类号: |
| 基金项目:国家自然科学基金项目资助(52477163) |
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| Evaluation and optimization of interaction capability of 5G base station virtual power plants based on hierarchical aggregation |
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CHENG Zixia1,2, WAN Jiayuan1, CHAI Xuzheng3
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1. School of Electrical and Information Engineering, Zhengzhou University, Zhengzhou 450001, China; 2. College of
Energy and Power Engineering, Xinjiang Railway Vocational and Technical College, Hami 839000, China;
3. State Grid Xuchang Power Supply Company, Xuchang 461000, China
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| Abstract: |
| To address the challenges in coordinating communication service constraints and power regulation, as well as the insufficient accuracy in quantifying regulation capability when 5G base station virtual power plants (VPPs) participate in grid interaction, a hierarchical aggregation-based method for interaction capability evaluation and optimization of 5G base station VPPs is proposed. First, considering the operational characteristics of 5G base stations, a hierarchical aggregation model consisting of “a single base station layer, a base station cluster layer, and a VPP multi-energy aggregation layer” is established, and the evaluation indices and calculation procedures of regulation capability at different levels are clarified. Then, under the constraints of communication service quality (quality of service, QoS), an optimal scheduling model incorporating base station energy storage is formulated, and the grey wolf optimizer (GWO) is introduced to achieve coordinated optimization under multiple constraints. Finally, simulation analyses are conducted to verify the proposed method. The results demonstrate that the proposed approach can effectively enhance the regulation flexibility and economic performance of 5G base station VPPs, providing technical support for coordinated operation between communication networks and power systems. |
| Key words: 5G base station virtual power plant hierarchical aggregation grey wolf optimizer |
