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Two-stage robust optimization of a virtual power plant considering a refined demand response

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  • Liu, Jinpeng
  • Peng, Jinchun
  • Liu, Hushihan
  • Deng, Jiaming
  • Song, Xiaohua

Abstract

A reasonable demand response strategy and flexible resource planning technology are the key methods for constructing new power systems. Based on this, a virtual power plant economic optimization model considering a refined demand response strategy is proposed. First, considering the regulatory characteristics of flexible loads and the satisfaction degree of residents, flexible loads are finely classified, and a demand response model is constructed. Second, considering the power uncertainty of wind turbines and photovoltaics in virtual power plants, a two-stage robust optimization model with a min–max–min structure is constructed; then, a transformation method of fuzzy sets and subproblems is proposed to improve the solution efficiency. Finally, the total operating cost of virtual power plants under the deviation of power forecasts and fluctuations in intraday electricity prices is analysed. The simulation results reveal that refined load classification can reduce the system day-ahead operating cost by 7.12 %; the proposed two-stage robust optimization model reduces the total real time operating cost by 0.81–6.39 % compared to the deterministic optimization model.

Suggested Citation

  • Liu, Jinpeng & Peng, Jinchun & Liu, Hushihan & Deng, Jiaming & Song, Xiaohua, 2025. "Two-stage robust optimization of a virtual power plant considering a refined demand response," Energy, Elsevier, vol. 322(C).
    • Handle: RePEc:eee:energy:v:322:y:2025:i:c:s0360544225012022
    DOI: 10.1016/j.energy.2025.135560
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    1. Li, Qiang & Wei, Fanchao & Zhou, Yongcheng & Li, Jiajia & Zhou, Guowen & Wang, Zhonghao & Liu, Jinfu & Yan, Peigang & Yu, Daren, 2023. "A scheduling framework for VPP considering multiple uncertainties and flexible resources," Energy, Elsevier, vol. 282(C).
    2. Zhang, Xihai & Ge, Shaoyun & Liu, Hong & Zhou, Yue & He, Xingtang & Xu, Zhengyang, 2023. "Distributionally robust optimization for peer-to-peer energy trading considering data-driven ambiguity sets," Applied Energy, Elsevier, vol. 331(C).
    3. Shams, Mohammad H. & Shahabi, Majid & MansourLakouraj, Mohammad & Shafie-khah, Miadreza & Catalão, João P.S., 2021. "Adjustable robust optimization approach for two-stage operation of energy hub-based microgrids," Energy, Elsevier, vol. 222(C).
    4. Cai, Pengcheng & Mi, Yang & Ma, Siyuan & Li, Hongzhong & Li, Dongdong & Wang, Peng, 2023. "Hierarchical game for integrated energy system and electricity-hydrogen hybrid charging station under distributionally robust optimization," Energy, Elsevier, vol. 283(C).
    5. Li, Yanbin & Sun, Yanting & Liu, Jiechao & Liu, Chang & Zhang, Feng, 2023. "A data driven robust optimization model for scheduling near-zero carbon emission power plant considering the wind power output uncertainties and electricity-carbon market," Energy, Elsevier, vol. 279(C).
    6. Kong, Xiangyu & Sun, Yuce & Khan, Muhammad Ahmad & Zheng, Lin & Qin, Junda & Ji, Xiaotong, 2024. "Cyber-physical system planning for VPPs supporting frequency regulation considering hierarchical control and multidimensional uncertainties," Applied Energy, Elsevier, vol. 353(PB).
    7. Kong, Xiangyu & Lu, Wenqi & Wu, Jianzhong & Wang, Chengshan & Zhao, Xv & Hu, Wei & Shen, Yu, 2023. "Real-time pricing method for VPP demand response based on PER-DDPG algorithm," Energy, Elsevier, vol. 271(C).
    8. Zhang, M.Y. & Chen, J.J. & Yang, Z.J. & Peng, K. & Zhao, Y.L. & Zhang, X.H., 2021. "Stochastic day-ahead scheduling of irrigation system integrated agricultural microgrid with pumped storage and uncertain wind power," Energy, Elsevier, vol. 237(C).
    9. Wang, Luhao & Zhang, Bingying & Li, Qiqiang & Song, Wen & Li, Guanguan, 2019. "Robust distributed optimization for energy dispatch of multi-stakeholder multiple microgrids under uncertainty," Applied Energy, Elsevier, vol. 255(C).
    10. Chen, Diyi & Liu, Si & Ma, Xiaoyi, 2013. "Modeling, nonlinear dynamical analysis of a novel power system with random wind power and it's control," Energy, Elsevier, vol. 53(C), pages 139-146.
    11. Monir Sadat AlDavood & Abolfazl Mehbodniya & Julian L. Webber & Mohammad Ensaf & Mahdi Azimian, 2022. "Robust Optimization-Based Optimal Operation of Islanded Microgrid Considering Demand Response," Sustainability, MDPI, vol. 14(21), pages 1-17, October.
    Full references (including those not matched with items on IDEAS)

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