IDEAS home Printed from https://ideas.repec.org/a/gam/jeners/v12y2019i18p3498-d266266.html
   My bibliography  Save this article

Power Distribution Strategy of Microgrid Hybrid Energy Storage System Based on Improved Hierarchical Control

Author

Listed:
  • Tiezhou Wu

    (Hubei Key Laboratory for High-efficiency Utilization of Solar Energy and Operation Control of Energy Storage System, Hubei University of Technology, Wuhan 430068, China)

  • Wenshan Yu

    (Hubei Key Laboratory for High-efficiency Utilization of Solar Energy and Operation Control of Energy Storage System, Hubei University of Technology, Wuhan 430068, China)

  • Lujun Wang

    (Hubei Key Laboratory for High-efficiency Utilization of Solar Energy and Operation Control of Energy Storage System, Hubei University of Technology, Wuhan 430068, China)

  • Linxin Guo

    (Hanjiang Water Resources & Hydropower Group Co., Ltd., Danjiangkou Hydropower Plant, Danjiangkou 442700, China)

  • Zhiquan Tang

    (Hanjiang Water Resources & Hydropower Group Co., Ltd., Danjiangkou Hydropower Plant, Danjiangkou 442700, China)

Abstract

Traditional hierarchical control of the microgrid does not consider the energy storage status of a distributed hybrid energy storage system. This leads to the inconsistency of the remaining capacity of the energy storage system in the process of system operation, which is not conducive to the safe and stable operation of the system. In this paper, an improved hierarchical control strategy is proposed: the first allocation layer completes the allocation between the distribution energy storage systems considering the state of hybrid energy storage systems, and the second allocation layer realizes the allocation within the hybrid energy storage systems based on variable time constant low-pass filtering. Considering the extreme conditions of energy storage systems, the transfer current is introduced in the second allocation process. The SOC (stage of charge) of the supercapacitor is between 40% and 60%, which ensures that the supercapacitor has enough margin to respond to the power demand. An example of a 300 MW photovoltaic microgrid system in a certain area is analyzed. Compared with the traditional hierarchical control, the proposed control strategy can reduce the SOC change of a hybrid energy storage system by 9% under the same conditions, and make the supercapacitor active after power stabilization, which is helpful to the stable operation of the microgrid.

Suggested Citation

  • Tiezhou Wu & Wenshan Yu & Lujun Wang & Linxin Guo & Zhiquan Tang, 2019. "Power Distribution Strategy of Microgrid Hybrid Energy Storage System Based on Improved Hierarchical Control," Energies, MDPI, vol. 12(18), pages 1-14, September.
  • Handle: RePEc:gam:jeners:v:12:y:2019:i:18:p:3498-:d:266266
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1996-1073/12/18/3498/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/1996-1073/12/18/3498/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Pan Wu & Wentao Huang & Nengling Tai & Zhoujun Ma & Xiaodong Zheng & Yong Zhang, 2019. "A Multi-Layer Coordinated Control Scheme to Improve the Operation Friendliness of Grid-Connected Multiple Microgrids," Energies, MDPI, vol. 12(2), pages 1-21, January.
    2. Li, Jianwei & Xiong, Rui & Mu, Hao & Cornélusse, Bertrand & Vanderbemden, Philippe & Ernst, Damien & Yuan, Weijia, 2018. "Design and real-time test of a hybrid energy storage system in the microgrid with the benefit of improving the battery lifetime," Applied Energy, Elsevier, vol. 218(C), pages 470-478.
    3. João Faria & José Pombo & Maria do Rosário Calado & Sílvio Mariano, 2019. "Power Management Control Strategy Based on Artificial Neural Networks for Standalone PV Applications with a Hybrid Energy Storage System," Energies, MDPI, vol. 12(5), pages 1-24, March.
    4. Zhang, Yi & Xu, Yujie & Guo, Huan & Zhang, Xinjing & Guo, Cong & Chen, Haisheng, 2018. "A hybrid energy storage system with optimized operating strategy for mitigating wind power fluctuations," Renewable Energy, Elsevier, vol. 125(C), pages 121-132.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Gustavo Navarro & Jorge Torres & Marcos Blanco & Jorge Nájera & Miguel Santos-Herran & Marcos Lafoz, 2021. "Present and Future of Supercapacitor Technology Applied to Powertrains, Renewable Generation and Grid Connection Applications," Energies, MDPI, vol. 14(11), pages 1-29, May.
    2. Miloud Rezkallah & Sanjeev Singh & Ambrish Chandra & Bhim Singh & Hussein Ibrahim, 2020. "Off-Grid System Configurations for Coordinated Control of Renewable Energy Sources," Energies, MDPI, vol. 13(18), pages 1-25, September.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Li, Shuangqi & He, Hongwen & Li, Jianwei, 2019. "Big data driven lithium-ion battery modeling method based on SDAE-ELM algorithm and data pre-processing technology," Applied Energy, Elsevier, vol. 242(C), pages 1259-1273.
    2. Mito, Mohamed T. & Ma, Xianghong & Albuflasa, Hanan & Davies, Philip A., 2019. "Reverse osmosis (RO) membrane desalination driven by wind and solar photovoltaic (PV) energy: State of the art and challenges for large-scale implementation," Renewable and Sustainable Energy Reviews, Elsevier, vol. 112(C), pages 669-685.
    3. Danijel Pavković & Mihael Cipek & Zdenko Kljaić & Tomislav Josip Mlinarić & Mario Hrgetić & Davor Zorc, 2018. "Damping Optimum-Based Design of Control Strategy Suitable for Battery/Ultracapacitor Electric Vehicles," Energies, MDPI, vol. 11(10), pages 1-26, October.
    4. Chrispin Tumba Tshiani & Patrice Umenne, 2022. "The Impact of the Electric Double-Layer Capacitor (EDLC) in Reducing Stress and Improving Battery Lifespan in a Hybrid Energy Storage System (HESS) System," Energies, MDPI, vol. 15(22), pages 1-19, November.
    5. Fuquan Zhao & Fanlong Bai & Xinglong Liu & Zongwei Liu, 2022. "A Review on Renewable Energy Transition under China’s Carbon Neutrality Target," Sustainability, MDPI, vol. 14(22), pages 1-27, November.
    6. Ding, Jie & Xu, Yujie & Chen, Haisheng & Sun, Wenwen & Hu, Shan & Sun, Shuang, 2019. "Value and economic estimation model for grid-scale energy storage in monopoly power markets," Applied Energy, Elsevier, vol. 240(C), pages 986-1002.
    7. Yi Yan & Xuerui Wang & Ke Li & Xiaopeng Kang & Weizheng Kong & Hongcai Dai, 2022. "Tri-Level Integrated Optimization Design Method of a CCHP Microgrid with Composite Energy Storage," Sustainability, MDPI, vol. 14(9), pages 1-29, April.
    8. João Faria & João Fermeiro & José Pombo & Maria Calado & Sílvio Mariano, 2020. "Proportional Resonant Current Control and Output-Filter Design Optimization for Grid-Tied Inverters Using Grey Wolf Optimizer," Energies, MDPI, vol. 13(8), pages 1-18, April.
    9. Xiaofei Zhang & Hongbin Ma, 2019. "Data-Driven Model-Free Adaptive Control Based on Error Minimized Regularized Online Sequential Extreme Learning Machine," Energies, MDPI, vol. 12(17), pages 1-17, August.
    10. Shi, Jing & Xu, Ying & Liao, Meng & Guo, Shuqiang & Li, Yuanyuan & Ren, Li & Su, Rongyu & Li, Shujian & Zhou, Xiao & Tang, Yuejin, 2019. "Integrated design method for superconducting magnetic energy storage considering the high frequency pulse width modulation pulse voltage on magnet," Applied Energy, Elsevier, vol. 248(C), pages 1-17.
    11. Wei Zhang & Ming Zhong & Junfei Han & Yumei Sun & Yang Wang, 2022. "Research on the strategy of lithium-ion battery–supercapacitor hybrid energy storage to suppress power fluctuation of direct current microgrid [Load frequency control of a novel renewable energy in," International Journal of Low-Carbon Technologies, Oxford University Press, vol. 17, pages 1012-1017.
    12. Qi, Nanjian & Yin, Yajiang & Dai, Keren & Wu, Chengjun & Wang, Xiaofeng & You, Zheng, 2021. "Comprehensive optimized hybrid energy storage system for long-life solar-powered wireless sensor network nodes," Applied Energy, Elsevier, vol. 290(C).
    13. Guo, Huan & Xu, Yujie & Kang, Haoyuan & Guo, Wenbing & Liu, Yu & Zhang, Xinjing & Zhou, Xuezhi & Chen, Haisheng, 2023. "From theory to practice: Evaluating the thermodynamic design landscape of compressed air energy storage systems," Applied Energy, Elsevier, vol. 352(C).
    14. Xu, Qingqing & Wu, Yuhang & Zheng, Wenpei & Gong, Yunhua & Dubljevic, Stevan, 2023. "Modeling and dynamic safety control of compressed air energy storage system," Renewable Energy, Elsevier, vol. 208(C), pages 203-213.
    15. Lei Zhang & Yingqi Liu & Beibei Pang & Bingxiang Sun & Ari Kokko, 2020. "Second Use Value of China’s New Energy Vehicle Battery: A View Based on Multi-Scenario Simulation," Sustainability, MDPI, vol. 12(1), pages 1-25, January.
    16. Akram, Umer & Nadarajah, Mithulananthan & Shah, Rakibuzzaman & Milano, Federico, 2020. "A review on rapid responsive energy storage technologies for frequency regulation in modern power systems," Renewable and Sustainable Energy Reviews, Elsevier, vol. 120(C).
    17. He, Qing & Liu, Hui & Hao, Yinping & Liu, Yaning & Liu, Wenyi, 2018. "Thermodynamic analysis of a novel supercritical compressed carbon dioxide energy storage system through advanced exergy analysis," Renewable Energy, Elsevier, vol. 127(C), pages 835-849.
    18. Pavlos Papageorgiou & Konstantinos Oureilidis & Anna Tsakiri & Georgios Christoforidis, 2023. "A Modified Decentralized Droop Control Method to Eliminate Battery Short-Term Operation in a Hybrid Supercapacitor/Battery Energy Storage System," Energies, MDPI, vol. 16(6), pages 1-21, March.
    19. Takele Ferede Agajie & Armand Fopah-Lele & Ahmed Ali & Isaac Amoussou & Baseem Khan & Mahmoud Elsisi & Wirnkar Basil Nsanyuy & Om Prakash Mahela & Roberto Marcelo Álvarez & Emmanuel Tanyi, 2023. "Integration of Superconducting Magnetic Energy Storage for Fast-Response Storage in a Hybrid Solar PV-Biogas with Pumped-Hydro Energy Storage Power Plant," Sustainability, MDPI, vol. 15(13), pages 1-30, July.
    20. Zhenxing Zhao & Kaijie Chen & Ying Chen & Yuxing Dai & Zeng Liu & Kuiyin Zhao & Huan Wang & Zishun Peng, 2021. "An Ultra-Fast Power Prediction Method Based on Simplified LSSVM Hyperparameters Optimization for PV Power Smoothing," Energies, MDPI, vol. 14(18), pages 1-15, September.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jeners:v:12:y:2019:i:18:p:3498-:d:266266. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.