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Optimization algorithm for power-source arrangement that levels the fluctuations in wide-area networks of renewable energy

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  • Obara, Shin'ya
  • Ito, Yuji
  • Okada, Masaki

Abstract

Fluctuations in individual renewable-energy supplies are largely reduced by distributing the renewable energy over a wide-area transmission network. Therefore, a new analysis algorithm for determining the amount of renewable energy in a wide-area transmission network was developed in this study. Accounting for the power interchange in the transmission network and the energy storage in electric heat pumps and heat storage tanks, the objective function plans the arrangement of the electric power sources that maximizes the economic efficiency of the system. The developed algorithm was applied to Hokkaido, Japan. The areas and capacities of the introduced renewable energies, and the amount of electric power interchanged through the transmission line, were determined. The installed capacity and economic efficiency of the backup power supply and energy storage equipment (heat storage) were also investigated. In this area, the introductory rate of renewable energy was 39.5% of the total electricity production. Moreover, the cost of a distributed power-supply network was 9.99 × 1010 USD. The proposed system is equivalent to 1.88 years of Hokkaido's energy consumption.

Suggested Citation

  • Obara, Shin'ya & Ito, Yuji & Okada, Masaki, 2018. "Optimization algorithm for power-source arrangement that levels the fluctuations in wide-area networks of renewable energy," Energy, Elsevier, vol. 142(C), pages 447-461.
    • Handle: RePEc:eee:energy:v:142:y:2018:i:c:p:447-461
    DOI: 10.1016/j.energy.2017.10.038
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    References listed on IDEAS

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    Cited by:

    1. Okada, Masaki & Onishi, Terumi & Obara, Shin’ya, 2020. "A design algorithm for an electric power system using wide-area interconnection of renewable energy," Energy, Elsevier, vol. 193(C).
    2. Mohammed, Nooriya A. & Al-Bazi, Ammar, 2021. "Management of renewable energy production and distribution planning using agent-based modelling," Renewable Energy, Elsevier, vol. 164(C), pages 509-520.

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