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A New Battery Energy Storage Charging/Discharging Scheme for Wind Power Producers in Real-Time Markets

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  • Minh Y Nguyen

    (Seoul National University, Gwanak-ro 599, Gwanak-gu, Seoul 151-744, Korea)

  • Dinh Hung Nguyen

    (Seoul National University, Gwanak-ro 599, Gwanak-gu, Seoul 151-744, Korea)

  • Yong Tae Yoon

    (Seoul National University, Gwanak-ro 599, Gwanak-gu, Seoul 151-744, Korea)

Abstract

Under a deregulated environment, wind power producers are subject to many regulation costs due to the intermittence of natural resources and the accuracy limits of existing prediction tools. This paper addresses the operation (charging/discharging) problem of battery energy storage installed in a wind generation system in order to improve the value of wind power in the real-time market. Depending on the prediction of market prices and the probabilistic information of wind generation, wind power producers can schedule the battery energy storage for the next day in order to maximize the profit. In addition, by taking into account the expenses of using batteries, the proposed charging/discharging scheme is able to avoid the detrimental operation of battery energy storage which can lead to a significant reduction of battery lifetime, i.e. , uneconomical operation. The problem is formulated in a dynamic programming framework and solved by a dynamic programming backward algorithm. The proposed scheme is then applied to the study cases, and the results of simulation show its effectiveness.

Suggested Citation

  • Minh Y Nguyen & Dinh Hung Nguyen & Yong Tae Yoon, 2012. "A New Battery Energy Storage Charging/Discharging Scheme for Wind Power Producers in Real-Time Markets," Energies, MDPI, vol. 5(12), pages 1-14, December.
    • Handle: RePEc:gam:jeners:v:5:y:2012:i:12:p:5439-5452:d:22332
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    References listed on IDEAS

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    1. Munksgaard, Jesper & Morthorst, Poul Erik, 2008. "Wind power in the Danish liberalised power market--Policy measures, price impact and investor incentives," Energy Policy, Elsevier, vol. 36(10), pages 3940-3947, October.
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    Cited by:

    1. Pyeong-Ik Hwang & Seong-Chul Kwon & Sang-Yun Yun, 2018. "Schedule-Based Operation Method Using Market Data for an Energy Storage System of a Customer in the Ontario Electricity Market," Energies, MDPI, vol. 11(10), pages 1-26, October.
    2. Fengbing Li & Kaigui Xie & Jiangping Yang, 2015. "Optimization and Analysis of a Hybrid Energy Storage System in a Small-Scale Standalone Microgrid for Remote Area Power Supply (RAPS)," Energies, MDPI, vol. 8(6), pages 1-25, May.
    3. Syahrul Nizam Md Saad & Adriaan Hendrik van der Weijde, 2019. "Evaluating the Potential of Hosting Capacity Enhancement Using Integrated Grid Planning modeling Methods," Energies, MDPI, vol. 12(19), pages 1-23, September.
    4. Loukatou, Angeliki & Johnson, Paul & Howell, Sydney & Duck, Peter, 2021. "Optimal valuation of wind energy projects co-located with battery storage," Applied Energy, Elsevier, vol. 283(C).
    5. Mengying Chen & Yifeng Wang & Liang Yang & Fuqiang Han & Yuqi Hou & Haiyun Yan, 2018. "A Variable-Structure Multi-Resonant DC–DC Converter with Smooth Switching," Energies, MDPI, vol. 11(9), pages 1-21, August.
    6. Chun-Liang Liu & Yi-Shun Chiu & Yi-Hua Liu & Yeh-Hsiang Ho & Shu-Syuan Huang, 2013. "Optimization of a Fuzzy-Logic-Control-Based Five-Stage Battery Charger Using a Fuzzy-Based Taguchi Method," Energies, MDPI, vol. 6(7), pages 1-20, July.
    7. Ly, Sel & Xie, Jiahang & Wolter, Franz-Erich & Nguyen, Hung D. & Weng, Yu, 2023. "T-shape data and probabilistic remaining useful life prediction for Li-ion batteries using multiple non-crossing quantile long short-term memory," Applied Energy, Elsevier, vol. 349(C).
    8. Daniele Gallo & Carmine Landi & Mario Luiso & Rosario Morello, 2013. "Optimization of Experimental Model Parameter Identification for Energy Storage Systems," Energies, MDPI, vol. 6(9), pages 1-19, September.

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