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Optimal Scheduling of Energy Storage Using A New Priority-Based Smart Grid Control Method

Author

Listed:
  • Luis Galván

    (Electronical Engineering Department, University of Seville, 41092 Seville, Spain)

  • Juan M. Navarro

    (Electronical Engineering Department, University of Seville, 41092 Seville, Spain)

  • Eduardo Galván

    (Electronical Engineering Department, University of Seville, 41092 Seville, Spain)

  • Juan M. Carrasco

    (Electronical Engineering Department, University of Seville, 41092 Seville, Spain)

  • Andrés Alcántara

    (Electronical Engineering Department, University of Seville, 41092 Seville, Spain)

Abstract

This paper presents a method to optimally use an energy storage system (such as a battery) on a microgrid with load and photovoltaic generation. The purpose of the method is to employ the photovoltaic generation and energy storage systems to reduce the main grid bill, which includes an energy cost and a power peak cost. The method predicts the loads and generation power of each day, and then searches for an optimal storage behavior plan for the energy storage system according to these predictions. However, this plan is not followed in an open-loop control structure as in previous publications, but provided to a real-time decision algorithm, which also considers real power measures. This algorithm considers a series of device priorities in addition to the storage plan, which makes it robust enough to comply with unpredicted situations. The whole proposed method is implemented on a real-hardware test bench, with its different steps being distributed between a personal computer and a programmable logic controller according to their time scale. When compared to a different state-of-the-art method, the proposed method is concluded to better adjust the energy storage system usage to the photovoltaic generation and general consumption.

Suggested Citation

  • Luis Galván & Juan M. Navarro & Eduardo Galván & Juan M. Carrasco & Andrés Alcántara, 2019. "Optimal Scheduling of Energy Storage Using A New Priority-Based Smart Grid Control Method," Energies, MDPI, vol. 12(4), pages 1-17, February.
    • Handle: RePEc:gam:jeners:v:12:y:2019:i:4:p:579-:d:205346
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    References listed on IDEAS

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    1. Morais, Hugo & Kádár, Péter & Faria, Pedro & Vale, Zita A. & Khodr, H.M., 2010. "Optimal scheduling of a renewable micro-grid in an isolated load area using mixed-integer linear programming," Renewable Energy, Elsevier, vol. 35(1), pages 151-156.
    2. Yohwan Choi & Hongseok Kim, 2016. "Optimal Scheduling of Energy Storage System for Self-Sustainable Base Station Operation Considering Battery Wear-Out Cost," Energies, MDPI, vol. 9(6), pages 1-19, June.
    3. Yuqing Yang & Weige Zhang & Jiuchun Jiang & Mei Huang & Liyong Niu, 2015. "Optimal Scheduling of a Battery Energy Storage System with Electric Vehicles’ Auxiliary for a Distribution Network with Renewable Energy Integration," Energies, MDPI, vol. 8(10), pages 1-18, September.
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    Cited by:

    1. Marco Pasetti, 2021. "Assessing the Effectiveness of the Energy Storage Rule-Based Control in Reducing the Power Flow Uncertainties Caused by Distributed Photovoltaic Systems," Energies, MDPI, vol. 14(8), pages 1-25, April.
    2. Pedro Faria & Zita Vale, 2019. "Distributed Energy Resources Management 2018," Energies, MDPI, vol. 13(1), pages 1-4, December.
    3. Manzoor Ellahi & Ghulam Abbas & Irfan Khan & Paul Mario Koola & Mashood Nasir & Ali Raza & Umar Farooq, 2019. "Recent Approaches of Forecasting and Optimal Economic Dispatch to Overcome Intermittency of Wind and Photovoltaic (PV) Systems: A Review," Energies, MDPI, vol. 12(22), pages 1-30, November.
    4. Libor Dražan & René Križan & Miroslav Popela, 2021. "Design and Testing of a Low-Tech DEW Generator for Determining Electromagnetic Immunity of Standard Electronic Circuits," Energies, MDPI, vol. 14(11), pages 1-15, May.

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