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Renewable Energy Assisted Traffic Aware Cellular Base Station Energy Cooperation

Author

Listed:
  • Faran Ahmed

    (Department of Electrical Engineering, COMSATS Institute of Information Technology, Wah 47040, Pakistan)

  • Muhammad Naeem

    (Department of Electrical Engineering, COMSATS Institute of Information Technology, Wah 47040, Pakistan)

  • Waleed Ejaz

    (Department of Electrical and Computer Engineering, Ryerson University, Toronto, ON M5B 2K3, Canada)

  • Muhammad Iqbal

    (Department of Electrical Engineering, COMSATS Institute of Information Technology, Wah 47040, Pakistan)

  • Alagan Anpalagan

    (Department of Electrical and Computer Engineering, Ryerson University, Toronto, ON M5B 2K3, Canada)

  • Hyung Seok Kim

    (Department of Information and Communication Engineering, Sejong University, Seoul 05006, Korea)

Abstract

With global concern for climate change, and for cutting down the energy cost, especially in off grid areas, use of renewable energy has been gaining widespread attention in many areas including cellular communication. The base station (BS) has emerged as a strong candidate for the integration of renewable energy sources (RES), particularly solar and wind. The incorporation of renewable energy opens many possibilities for energy conservation through strategies such as energy cooperation between BSs during the off-peak hours, when the energy harvested from renewable energy sources may become surplus. In this paper, we present the case for cellular BSs enabled with renewable energy sources (RES) to have an arrangement in which the BS provide surplus energy to a neighboring BS, thus minimizing the use of conventional energy. A realistic objective is developed for northern region of Pakistan, which entails modeling of solar panels and wind-turbine according to the average solar irradiation and wind speed of the region. We also model the dynamic load of the BS, which depicts temporal fluctuations with traffic variations. Based on these models we initiate an energy cooperation scheme between the BS in which an energy cost minimization framework is mathematically modeled and solved through the interior point method algorithm. Results are obtained for different times of the year for different number of base stations showing respective energy cost savings.

Suggested Citation

  • Faran Ahmed & Muhammad Naeem & Waleed Ejaz & Muhammad Iqbal & Alagan Anpalagan & Hyung Seok Kim, 2018. "Renewable Energy Assisted Traffic Aware Cellular Base Station Energy Cooperation," Energies, MDPI, vol. 11(1), pages 1-19, January.
    • Handle: RePEc:gam:jeners:v:11:y:2018:i:1:p:99-:d:125177
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    References listed on IDEAS

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    4. Theo, Wai Lip & Lim, Jeng Shiun & Ho, Wai Shin & Hashim, Haslenda & Lee, Chew Tin, 2017. "Review of distributed generation (DG) system planning and optimisation techniques: Comparison of numerical and mathematical modelling methods," Renewable and Sustainable Energy Reviews, Elsevier, vol. 67(C), pages 531-573.
    5. Byung Moo Lee & Youngok Kim, 2016. "Design of an Energy Efficient Future Base Station with Large-Scale Antenna System," Energies, MDPI, vol. 9(12), pages 1-17, December.
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    Cited by:

    1. Peter Ozaveshe Oviroh & Tien-Chien Jen, 2018. "The Energy Cost Analysis of Hybrid Systems and Diesel Generators in Powering Selected Base Transceiver Station Locations in Nigeria," Energies, MDPI, vol. 11(3), pages 1-20, March.
    2. Khondoker Ziaul Islam & Md. Sanwar Hossain & B. M. Ruhul Amin & G. M. Shafiullah & Ferdous Sohel, 2022. "Renewable Energy-Based Energy-Efficient Off-Grid Base Stations for Heterogeneous Network," Energies, MDPI, vol. 16(1), pages 1-33, December.
    3. Mahshid Javidsharifi & Hamoun Pourroshanfekr & Tamas Kerekes & Dezso Sera & Sergiu Spataru & Josep M. Guerrero, 2021. "Optimum Sizing of Photovoltaic and Energy Storage Systems for Powering Green Base Stations in Cellular Networks," Energies, MDPI, vol. 14(7), pages 1-21, March.

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