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State-Of-The-Art in Microgrid-Integrated Distributed Energy Storage Sizing

Author

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  • Ibrahim Alsaidan

    (Department of Electrical and Computer Engineering, University of Denver, Denver, CO 80210, USA)

  • Abdulaziz Alanazi

    (Department of Electrical and Computer Engineering, University of Denver, Denver, CO 80210, USA)

  • Wenzhong Gao

    (Department of Electrical and Computer Engineering, University of Denver, Denver, CO 80210, USA)

  • Hongyu Wu

    (Department of Electrical and Computer Engineering, Kansas State University, Manhattan, KS 66506, USA)

  • Amin Khodaei

    (Department of Electrical and Computer Engineering, University of Denver, Denver, CO 80210, USA)

Abstract

Distributed energy storage (DES) plays an important role in microgrid operation and control, as it can potentially improve local reliability and resilience, reduce operation cost, and mitigate challenges caused by high penetration renewable generation. However, to ensure an acceptable economic and technical performance, DES must be optimally sized and placed. This paper reviews the existing DES sizing methods for microgrid applications and presents a generic sizing method that enables microgrid planners to efficiently determine the optimal DES size, technology, and location. The proposed method takes into consideration the impact of DES operation on its lifetime to enhance the obtained results accuracy and practicality. The presented model can be used for both grid-tied (considering both grid-connected and islanded modes) and isolated microgrids.

Suggested Citation

  • Ibrahim Alsaidan & Abdulaziz Alanazi & Wenzhong Gao & Hongyu Wu & Amin Khodaei, 2017. "State-Of-The-Art in Microgrid-Integrated Distributed Energy Storage Sizing," Energies, MDPI, vol. 10(9), pages 1-14, September.
    • Handle: RePEc:gam:jeners:v:10:y:2017:i:9:p:1421-:d:112213
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    References listed on IDEAS

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    1. Nan Zhou & Nian Liu & Jianhua Zhang & Jinyong Lei, 2016. "Multi-Objective Optimal Sizing for Battery Storage of PV-Based Microgrid with Demand Response," Energies, MDPI, vol. 9(8), pages 1-24, July.
    2. Fossati, Juan P. & Galarza, Ainhoa & Martín-Villate, Ander & Fontán, Luis, 2015. "A method for optimal sizing energy storage systems for microgrids," Renewable Energy, Elsevier, vol. 77(C), pages 539-549.
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    2. Ping Liu & Zexiang Cai & Peng Xie & Xiaohua Li & Yongjun Zhang, 2019. "A Computationally Efficient Optimization Method for Battery Storage in Grid-connected Microgrids Based on a Power Exchanging Process," Energies, MDPI, vol. 12(8), pages 1-19, April.
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    6. Xiao Qi & Yan Bai & Huanhuan Luo & Yiqing Zhang & Guiping Zhou & Zhonghua Wei, 2018. "Novel Distributed Optimal Control of Battery Energy Storage System in an Islanded Microgrid with Fast Frequency Recovery," Energies, MDPI, vol. 11(8), pages 1-18, July.
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    10. Bingyin Lei & Yue Ren & Huiyu Luan & Ruonan Dong & Xiuyuan Wang & Junli Liao & Shu Fang & Kaiye Gao, 2023. "A Review of Optimization for System Reliability of Microgrid," Mathematics, MDPI, vol. 11(4), pages 1-30, February.
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    13. Alvarado-Barrios, Lázaro & Rodríguez del Nozal, Álvaro & Boza Valerino, Juan & García Vera, Ignacio & Martínez-Ramos, Jose L., 2020. "Stochastic unit commitment in microgrids: Influence of the load forecasting error and the availability of energy storage," Renewable Energy, Elsevier, vol. 146(C), pages 2060-2069.
    14. Rehman, Waqas ur & Bo, Rui & Mehdipourpicha, Hossein & Kimball, Jonathan W., 2022. "Sizing battery energy storage and PV system in an extreme fast charging station considering uncertainties and battery degradation," Applied Energy, Elsevier, vol. 313(C).
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