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Improvement of energy supply configuration for telecommunication system in remote area s based on improved chaotic world cup optimization algorithm

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  • Li, Huan
  • Li, Kun
  • Zafetti, Nicholas
  • Gu, Jianfeng

Abstract

Generally, using the telecommunication industry in remote rural areas which can’t use the grid is difficult. This issue makes this industry to be extremely dependent on the diesel generators and battery banks for having backup resources. Despite, the unreliability and the environment impacts of these power supplies, using diesel generators is still popular. In this paper, a new clean and optimized configuration based on the proton exchange membrane fuel cell (PEMFC) along with an optimized boost converter unit is proposed for obtaining a reliable source to supply the telecom towers. Using the proposed optimized method makes the cost of telecom companies decreasing. In this study, a feedback controller based on a newly introduced optimization algorithm called improved chaos world cup optimization algorithm is proposed for optimal regulation of the converter unit. The proposed technique provides reliable and high-efficiency performance for the base transceiver station under oscillations on the telecom load and the output voltage of the PEMFC. Simulation results of the proposed optimization method are compared by the traditional Ziegler-Nichols based PI controller and final results showed the superiority of the proposed system.

Suggested Citation

  • Li, Huan & Li, Kun & Zafetti, Nicholas & Gu, Jianfeng, 2020. "Improvement of energy supply configuration for telecommunication system in remote area s based on improved chaotic world cup optimization algorithm," Energy, Elsevier, vol. 192(C).
    • Handle: RePEc:eee:energy:v:192:y:2020:i:c:s0360544219323096
    DOI: 10.1016/j.energy.2019.116614
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    References listed on IDEAS

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    Cited by:

    1. Rezk, Hegazy & Ferahtia, Seydali & Djeroui, Ali & Chouder, Aissa & Houari, Azeddine & Machmoum, Mohamed & Abdelkareem, Mohammad Ali, 2022. "Optimal parameter estimation strategy of PEM fuel cell using gradient-based optimizer," Energy, Elsevier, vol. 239(PC).
    2. Yin, Linfei & Wu, Yunzhi, 2022. "Mode-decomposition memory reinforcement network strategy for smart generation control in multi-area power systems containing renewable energy," Applied Energy, Elsevier, vol. 307(C).
    3. Yang, Zixuan & Liu, Qian & Zhang, Leiyu & Dai, Jialei & Razmjooy, Navid, 2020. "Model parameter estimation of the PEMFCs using improved Barnacles Mating Optimization algorithm," Energy, Elsevier, vol. 212(C).
    4. Zeljković, Čedomir & Mršić, Predrag & Erceg, Bojan & Lekić, Đorđe & Kitić, Nemanja & Matić, Petar, 2022. "Optimal sizing of photovoltaic-wind-diesel-battery power supply for mobile telephony base stations," Energy, Elsevier, vol. 242(C).

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