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Optimal scheduling of virtual power plants with reversible solid oxide cells in the electricity market

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  • Wang, Qiujie
  • Leng, Zihao
  • Tan, Hong
  • Mohamed, Mohamed A.
  • Jin, Tao

Abstract

Virtual power plants (VPP) can act as an independent entity to aggregate different distributed resources to participate in the electricity market, which is an inevitable trend in building green and low-carbon power systems. To investigate the beneficial effect of bi-directional electric-hydrogen conversion on market trading and optimal scheduling of VPP, this paper presents an optimal scheduling method for VPP with reversible solid oxide cells (RSOC) in the electricity market. Firstly, according to the Butler-Volmer equation and Faraday law, the relationship between the hydrogen flow rate and the electric power is established, and the equivalent physical models of the two RSOC working modes are developed based on the relationship. Then, the optimal scheduling model of the VPP participating in the energy and reserve joint market is proposed based on the two-stage robust optimization theory. The system operator reserve demand is used to describe the uncertainty of the transactions between VPP and reserve market. Finally, the column and constraint generation (C&CG) algorithm is used to solve the two-stage robust scheduling model. The simulation results show that RSOC can effectively promote renewable energy consumption and improve the VPP operating profit. Where, the operating profit can be increased by 46.5 % and the wind power consumption rate can be increased by 3.4 %, compared with the non-hydrogen VPP. Furthermore, compared with the traditional conversion equipment, RSOC can increase the VPP operating profit by 2.3 % and the wind power consumption rate by 1.85 %.

Suggested Citation

  • Wang, Qiujie & Leng, Zihao & Tan, Hong & Mohamed, Mohamed A. & Jin, Tao, 2024. "Optimal scheduling of virtual power plants with reversible solid oxide cells in the electricity market," Renewable Energy, Elsevier, vol. 237(PC).
    • Handle: RePEc:eee:renene:v:237:y:2024:i:pc:s0960148124018275
    DOI: 10.1016/j.renene.2024.121759
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    References listed on IDEAS

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    1. Zhou, Kaile & Peng, Ning & Yin, Hui & Hu, Rong, 2023. "Urban virtual power plant operation optimization with incentive-based demand response," Energy, Elsevier, vol. 282(C).
    2. Razmi, Amir Reza & Hanifi, Amir Reza & Shahbakhti, Mahdi, 2023. "Design, thermodynamic, and economic analyses of a green hydrogen storage concept based on solid oxide electrolyzer/fuel cells and heliostat solar field," Renewable Energy, Elsevier, vol. 215(C).
    3. Tan, Hong & Yan, Wei & Ren, Zhouyang & Wang, Qiujie & Mohamed, Mohamed A., 2022. "Distributionally robust operation for integrated rural energy systems with broiler houses," Energy, Elsevier, vol. 254(PC).
    4. Tan, Hong & Li, Zhenxing & Wang, Qiujie & Mohamed, Mohamed A., 2023. "A novel forecast scenario-based robust energy management method for integrated rural energy systems with greenhouses," Applied Energy, Elsevier, vol. 330(PB).
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    Cited by:

    1. Ruslan V. Fedorov & Igor I. Shepelev & Mariia A. Malyoshina & Dmitry A. Generalov & Vyacheslav V. Sherkunov & Valeriy V. Sapunov, 2025. "Software Package for Optimization of Burner Devices on Dispersed Working Fluids," Energies, MDPI, vol. 18(4), pages 1-29, February.

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