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A Grid-Connected Microgrid Model and Optimal Scheduling Strategy Based on Hybrid Energy Storage System and Demand-Side Response

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Listed:
  • Yaqian Jing

    (School of Management, Guizhou University, Guiyang 550025, China)

  • Honglei Wang

    (School of Management, Guizhou University, Guiyang 550025, China
    Key Laboratory of “Internet+” Collaborative Intelligent Manufacturing in Guizhou Province, Guiyang 550025, China)

  • Yujie Hu

    (School of Management, Guizhou University, Guiyang 550025, China
    Key Laboratory of “Internet+” Collaborative Intelligent Manufacturing in Guizhou Province, Guiyang 550025, China)

  • Chengjiang Li

    (School of Management, Guizhou University, Guiyang 550025, China
    Key Laboratory of “Internet+” Collaborative Intelligent Manufacturing in Guizhou Province, Guiyang 550025, China)

Abstract

The power gap between supply and demand in the microgrid caused by the uncertainty of wind and solar output and users’ electricity consumption needs to be absorbed by the hybrid energy storage devices and the demand-side electricity price response. To maximize the service life of the lithium battery pack, this paper optimizes a reasonable ratio of the supercapacitor pack’s daily charge and discharge times to the daily cycle times of the lithium battery pack. The model construction includes two parts: power prediction and multi-objective optimization modeling. In the case study, a microgrid district under the Guizhou Power Grid is analyzed and discussed. Based on the predicted wind output, solar output, and load demand on a certain day, the optimal scheduling results have been obtained. On the one hand, a reasonable ratio regarding the daily charge and discharge times of hybrid energy storage devices has been obtained under the optimized parameter k in the model. Correspondingly, the daily operation and maintenance of the lithium battery pack is minimum. On the other hand, when the hybrid energy storage devices and demand-side electricity price response are included and not, the changes on the supply and demand sides (a) and of three evaluation indicators (b) are compared, respectively. Thus, the effectiveness of the model in this paper is verified.

Suggested Citation

  • Yaqian Jing & Honglei Wang & Yujie Hu & Chengjiang Li, 2022. "A Grid-Connected Microgrid Model and Optimal Scheduling Strategy Based on Hybrid Energy Storage System and Demand-Side Response," Energies, MDPI, vol. 15(3), pages 1-21, January.
    • Handle: RePEc:gam:jeners:v:15:y:2022:i:3:p:1060-:d:739509
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    References listed on IDEAS

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    1. Shaozhen Jin & Zhizhong Mao & Hongru Li & Wenhai Qi, 2018. "Dynamic Operation Management of a Renewable Microgrid including Battery Energy Storage," Mathematical Problems in Engineering, Hindawi, vol. 2018, pages 1-19, September.
    2. Byeong-Cheol Jeong & Dong-Hwan Shin & Jae-Beom Im & Jae-Young Park & Young-Jin Kim, 2019. "Implementation of Optimal Two-Stage Scheduling of Energy Storage System Based on Big-Data-Driven Forecasting—An Actual Case Study in a Campus Microgrid," Energies, MDPI, vol. 12(6), pages 1-20, March.
    3. Tiezhou Wu & Fanchao Ye & Yuehong Su & Yubo Wang & Saffa Riffat, 2020. "Coordinated control strategy of DC microgrid with hybrid energy storage system to smooth power output fluctuation," International Journal of Low-Carbon Technologies, Oxford University Press, vol. 15(1), pages 46-54.
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    Cited by:

    1. Ji, Jie & Zhou, Mengxiong & Guo, Renwei & Tang, Jiankang & Su, Jiaoyue & Huang, Hui & Sun, Na & Nazir, Muhammad Shahzad & Wang, Yaodong, 2023. "A electric power optimal scheduling study of hybrid energy storage system integrated load prediction technology considering ageing mechanism," Renewable Energy, Elsevier, vol. 215(C).
    2. Paweł Dworak & Andrzej Mrozik & Agata Korzelecka-Orkisz & Adam Tański & Krzysztof Formicki, 2023. "Energy Self-Sufficiency of a Salmonids Breeding Facility in the Recirculating Aquaculture System," Energies, MDPI, vol. 16(6), pages 1-22, March.

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