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Implementation of Optimal Scheduling Algorithm for Multi-Functional Battery Energy Storage System

Author

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  • Hee-Jun Cha

    (Department of Electrical Engineering, Inha University, 100, Inha-ro, Nam-gu, Incheon 402-751, Korea)

  • Sung-Eun Lee

    (Korea Electric Power Research Institute (KEPRI), Korea Electric Power Company (KEPCO), 105 Munji-Ro, Yuseong-gu, Daejeon 34056, Korea)

  • Dongjun Won

    (Department of Electrical Engineering, Inha University, 100, Inha-ro, Nam-gu, Incheon 402-751, Korea)

Abstract

Energy storage system (ESS) can play a positive role in the power system due to its ability to store, charge and discharge energy. Additionally, it can be installed in various capacities, so it can be used in the transmission and distribution system and even at home. In this paper, the proposed algorithm for economic optimal scheduling of ESS linked to transmission systems in the Korean electricity market is proposed and incorporated into the BESS (battery energy storage system) demonstration test center. The proposed algorithm considers the energy arbitrage operation through SMP (system marginal price) and operation considering the REC (renewable energy certification) weight of the connected wind farm and frequency regulation service. In addition, the proposed algorithm was developed so that the SOC (state-of-charge) of the ESS could be separated into two virtual SOCs to participate in different markets and generate revenue. The proposed algorithm was simulated and verified through Matlab and loaded into the demonstration system using the Matlab “Runtime” function.

Suggested Citation

  • Hee-Jun Cha & Sung-Eun Lee & Dongjun Won, 2019. "Implementation of Optimal Scheduling Algorithm for Multi-Functional Battery Energy Storage System," Energies, MDPI, vol. 12(7), pages 1-17, April.
    • Handle: RePEc:gam:jeners:v:12:y:2019:i:7:p:1339-:d:220835
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    References listed on IDEAS

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    1. Douglas Halamay & Michael Antonishen & Kelcey Lajoie & Arne Bostrom & Ted K. A. Brekken, 2014. "Improving Wind Farm Dispatchability Using Model Predictive Control for Optimal Operation of Grid-Scale Energy Storage," Energies, MDPI, vol. 7(9), pages 1-16, September.
    2. Sung-Min Cho & Sang-Yun Yun, 2017. "Optimal Power Assignment of Energy Storage Systems to Improve the Energy Storage Efficiency for Frequency Regulation," Energies, MDPI, vol. 10(12), pages 1-13, December.
    3. Wonchang Hur & Yongma Moon & Kwangsup Shin & Wooje Kim & Suchul Nam & Kijun Park, 2015. "Economic Value of Li-ion Energy Storage System in Frequency Regulation Application from Utility Firm’s Perspective in Korea," Energies, MDPI, vol. 8(6), pages 1-18, May.
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    Cited by:

    1. Hyun Cheol Jeong & Jaesung Jung & Byung O Kang, 2020. "Development of Operational Strategies of Energy Storage System Using Classification of Customer Load Profiles under Time-of-Use Tariffs in South Korea," Energies, MDPI, vol. 13(7), pages 1-17, April.
    2. Alba Leduchowicz-Municio & Miguel Edgar Morales Udaeta & André Luiz Veiga Gimenes & Tuo Ji & Victor Baiochi Riboldi, 2022. "Socio-Environmental Evaluation of MV Commercial Time-Shift Application Based on Battery Energy Storage Systems," Energies, MDPI, vol. 15(14), pages 1-21, July.
    3. Harun Or Rashid Howlader & Oludamilare Bode Adewuyi & Ying-Yi Hong & Paras Mandal & Ashraf Mohamed Hemeida & Tomonobu Senjyu, 2019. "Energy Storage System Analysis Review for Optimal Unit Commitment," Energies, MDPI, vol. 13(1), pages 1-21, December.

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