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Energy Management Strategy for Distributed Photovoltaic 5G Base Station DC Microgrid Integrated with the CF-P&O-INC MPPT Algorithm

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  • Zheng Cai

    (School of Computer and Electronic Information, Guangxi University, Nanning 530004, China
    The Guangxi Key Laboratory of Multimedia Communications and Network Technology, Guangxi University, Nanning 530004, China)

  • Yuben Tang

    (School of Electrical Engineering, Guangxi University, Nanning 530004, China)

  • Wenhao Guo

    (The Guangxi Key Laboratory of Multimedia Communications and Network Technology, Guangxi University, Nanning 530004, China
    School of Electrical Engineering, Guangxi University, Nanning 530004, China)

  • Tingting Chen

    (School of Computer and Electronic Information, Guangxi University, Nanning 530004, China
    The Guangxi Key Laboratory of Multimedia Communications and Network Technology, Guangxi University, Nanning 530004, China)

  • Hanbo Zheng

    (School of Electrical Engineering, Guangxi University, Nanning 530004, China)

  • Tuanfa Qin

    (School of Computer and Electronic Information, Guangxi University, Nanning 530004, China
    The Guangxi Key Laboratory of Multimedia Communications and Network Technology, Guangxi University, Nanning 530004, China)

Abstract

With its technical advantages of high speed, low latency, and broad connectivity, fifth-generation mobile communication technology has brought about unprecedented development in numerous vertical application scenarios. However, the high energy consumption and expansion difficulties of 5G infrastructure have become the main obstacles restricting its widespread application. Therefore, aiming to optimize the energy utilization efficiency of 5G base stations, a novel distributed photovoltaic 5G base station DC microgrid structure and an energy management strategy based on the Curve Fitting–Perturb and Observe–Incremental Conductance (CF-P&O-INC) Maximum Power Point Tracking (MPPT) algorithm from the perspectives of energy and information flows are proposed. Simulation results show that the proposed MPPT algorithm can increase the efficiency to 99.95% and 99.82% under uniform irradiation and partial shading, respectively. Under the proposed strategy, when the base station load changes drastically, the voltage fluctuation of the DC bus is less than 1.875%, and returns to a steady state within 0.07s, alleviating the high energy consumption of 5G base stations effectively and achieving coordinated optimization management of various types of energy in multi-source power supply systems.

Suggested Citation

  • Zheng Cai & Yuben Tang & Wenhao Guo & Tingting Chen & Hanbo Zheng & Tuanfa Qin, 2024. "Energy Management Strategy for Distributed Photovoltaic 5G Base Station DC Microgrid Integrated with the CF-P&O-INC MPPT Algorithm," Energies, MDPI, vol. 17(13), pages 1-18, July.
    • Handle: RePEc:gam:jeners:v:17:y:2024:i:13:p:3258-:d:1427766
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    References listed on IDEAS

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    1. Priyanka Mishra & Ghanshyam Singh, 2023. "Energy Management Systems in Sustainable Smart Cities Based on the Internet of Energy: A Technical Review," Energies, MDPI, vol. 16(19), pages 1-36, September.
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