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An improved min-max power dispatching method for integration of variable renewable energy

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  • Wang, Wei
  • Sun, Bo
  • Li, Hailong
  • Sun, Qie
  • Wennersten, Ronald

Abstract

High uncertainty and large fluctuation of variable renewable energy create enormous challenges to planning and operation of integrated energy systems. To overcome these problems, this paper proposed an improved min-max dispatching method. In the meantime, a control algorithm for short-term power dispatching was proposed and implemented to smoothen the power dispatching between two neighboring dispatching intervals. The improved min-max dispatching method was applied to a 1 kW experimental PV system with real-time data. The optimal capacity of the battery energy storage system obtained by the improved min-max method is 40% smaller than the volume obtained by the modified min-max method. Regarding the operation of the BESS, the average depth of discharge is 0.5988, which is 7.06% higher than the operation performance with the alternative dispatching method. The results clearly indicate that improved min-max dispatching method is a very effective approach for managing grid-connected integrated energy systems and promoting penetration of variable renewable energies.

Suggested Citation

  • Wang, Wei & Sun, Bo & Li, Hailong & Sun, Qie & Wennersten, Ronald, 2020. "An improved min-max power dispatching method for integration of variable renewable energy," Applied Energy, Elsevier, vol. 276(C).
    • Handle: RePEc:eee:appene:v:276:y:2020:i:c:s0306261920309429
    DOI: 10.1016/j.apenergy.2020.115430
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    References listed on IDEAS

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    Cited by:

    1. Jin, Jingliang & Wen, Qinglan & Zhao, Liya & Zhou, Chaoyang & Guo, Xiaojun, 2023. "Measuring environmental performance of power dispatch influenced by low-carbon approaches," Renewable Energy, Elsevier, vol. 209(C), pages 325-339.
    2. Jin, Jingliang & Wen, Qinglan & Cheng, Siqi & Qiu, Yaru & Zhang, Xianyue & Guo, Xiaojun, 2022. "Optimization of carbon emission reduction paths in the low-carbon power dispatching process," Renewable Energy, Elsevier, vol. 188(C), pages 425-436.
    3. Bin Zhang & Junbo Yang & Sule Tian & Qingxi Huang & Wei Wang & Qie Sun & Xiaohan Ren, 2023. "Techno-Economic Evaluation of a Compressed CO 2 Energy Storage System for Load Shifting Based on Dynamic Modelling," Energies, MDPI, vol. 16(23), pages 1-15, December.
    4. Oskouei, Morteza Zare & Mohammadi-Ivatloo, Behnam & Abapour, Mehdi & Shafiee, Mahmood & Anvari-Moghaddam, Amjad, 2021. "Privacy-preserving mechanism for collaborative operation of high-renewable power systems and industrial energy hubs," Applied Energy, Elsevier, vol. 283(C).

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