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Optimal Operation and Management of Smart Grid System with LPC and BESS in Fault Conditions

Author

Listed:
  • Ryuto Shigenobu

    (Faculty of Engineering, University of the Ryukyus, 1 Senbaru Nishihara-cho Nakagami, Okinawa 903-0213, Japan)

  • Ahmad Samim Noorzad

    (Faculty of Engineering, University of the Ryukyus, 1 Senbaru Nishihara-cho Nakagami, Okinawa 903-0213, Japan
    These authors contributed equally to this work.)

  • Cirio Muarapaz

    (Faculty of Engineering, University of the Ryukyus, 1 Senbaru Nishihara-cho Nakagami, Okinawa 903-0213, Japan
    These authors contributed equally to this work.)

  • Atsushi Yona

    (Faculty of Engineering, University of the Ryukyus, 1 Senbaru Nishihara-cho Nakagami, Okinawa 903-0213, Japan
    These authors contributed equally to this work.)

  • Tomonobu Senjyu

    (Faculty of Engineering, University of the Ryukyus, 1 Senbaru Nishihara-cho Nakagami, Okinawa 903-0213, Japan
    These authors contributed equally to this work.)

Abstract

Distributed generators (DG) using renewable energy sources (RESs) have been attracting special attention within distribution systems. However, a large amount of DG penetration causes voltage deviation and reverse power flow in the smart grid. Therefore, the smart grid needs a solution for voltage control, power flow control and power outage prevention. This paper proposes a decision technique of optimal reference scheduling for a battery energy storage system (BESS), inverters interfacing with a DG and voltage control devices for optimal operation. Moreover, the reconfiguration of the distribution system is made possible by the installation of a loop power flow controller (LPC). Two separate simulations are provided to maintain the reliability in the stable power supply and economical aspects. First, the effectiveness of the smart grid with installed BESS or LPC devices is demonstrated in fault situations. Second, the active smart grid using LCPs is proposed. Real-time techniques of the dual scheduling algorithm are applied to the system. The aforementioned control objective is formulated and solved using the particle swarm optimization (PSO) algorithm with an adaptive inertia weight (AIW) function. The effectiveness of the optimal operation in ordinal and fault situations is verified by numerical simulations.

Suggested Citation

  • Ryuto Shigenobu & Ahmad Samim Noorzad & Cirio Muarapaz & Atsushi Yona & Tomonobu Senjyu, 2016. "Optimal Operation and Management of Smart Grid System with LPC and BESS in Fault Conditions," Sustainability, MDPI, vol. 8(12), pages 1-19, December.
    • Handle: RePEc:gam:jsusta:v:8:y:2016:i:12:p:1282-:d:84676
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    Citations

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    Cited by:

    1. Moonsung Bae & Hwanik Lee & Byongjun Lee, 2017. "An Approach to Improve the Penetration of Sustainable Energy Using Optimal Transformer Tap Control," Sustainability, MDPI, vol. 9(9), pages 1-15, August.
    2. Jinwoo Jeong & Heewon Shin & Hwachang Song & Byongjun Lee, 2018. "A Countermeasure for Preventing Flexibility Deficit under High-Level Penetration of Renewable Energies: A Robust Optimization Approach," Sustainability, MDPI, vol. 10(11), pages 1-16, November.
    3. Ramin Sakipour & Hamdi Abdi, 2020. "Optimizing Battery Energy Storage System Data in the Presence of Wind Power Plants: A Comparative Study on Evolutionary Algorithms," Sustainability, MDPI, vol. 12(24), pages 1-21, December.

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