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Preserving operation privacy of peer-to-peer energy transaction based on Enhanced Benders Decomposition considering uncertainty of renewable energy generations

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  • Xia, Yuanxing
  • Xu, Qingshan
  • Tao, Siyu
  • Du, Pengwei
  • Ding, Yixing
  • Fang, Jicheng

Abstract

Peer-to-peer (P2P) energy transactions are getting much more popular recently due to the development of distributed generation technology. However, the private information of the market participants cannot be adequately preserved in the existing research. Therefore, a privacy-preserving operation model of P2P power transaction based on enhanced Benders decomposition (EBD) is proposed in this paper to schedule the exchanged energy among smart buildings optimally. In addition, an energy-sharing mechanism based on the Nash game is proposed to protect the prosumers’ privacy inside each building. The transactions in the distribution network and buildings are divided into system-centric and peer-centric, which are modeled as an outer-level problem and a set of inner-level problems. A Stackelberg-Nash framework is established to describe the relationship between the system operator and the smart buildings. Flexible loads inside each building resolve the trading deviations caused by renewable energy fluctuations. The flexibility requirements of each building are approximated with the linearized outer-level problem and the divided uncertainty regions. According to the simulation results of the modified 15-bus and 123-bus distribution networks, the building managers and distribution system operators manage to collaborate on operating to maximize the revenues of the prosumers of the entire network. The comparison results of the Accelerated linearized Alternating Direction Method of Multipliers (AADMM) and EBD validate the robustness and scalability of EBD applied in the trading framework. The flexibility requirements can be obtained within finite iterations.

Suggested Citation

  • Xia, Yuanxing & Xu, Qingshan & Tao, Siyu & Du, Pengwei & Ding, Yixing & Fang, Jicheng, 2022. "Preserving operation privacy of peer-to-peer energy transaction based on Enhanced Benders Decomposition considering uncertainty of renewable energy generations," Energy, Elsevier, vol. 250(C).
    • Handle: RePEc:eee:energy:v:250:y:2022:i:c:s0360544222004704
    DOI: 10.1016/j.energy.2022.123567
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    References listed on IDEAS

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    4. Jia, Hongjie & Wang, Xiaoyu & Jin, Xiaolong & Cheng, Lin & Mu, Yunfei & Yu, Xiaodan & Wei, Wei, 2024. "Optimal pricing of integrated community energy system for building prosumers with P2P multi-energy trading," Applied Energy, Elsevier, vol. 365(C).
    5. Wu, Chuantao & Zhou, Dezhi & Lin, Xiangning & Sui, Quan & Wei, Fanrong & Li, Zhengtian, 2022. "A novel energy cooperation framework for multi-island microgrids based on marine mobile energy storage systems," Energy, Elsevier, vol. 252(C).
    6. Al-Lawati, Razan A.H. & Faiz, Tasnim Ibn & Noor-E-Alam, Md., 2024. "A nationwide multi-location multi-resource stochastic programming based energy planning framework," Energy, Elsevier, vol. 295(C).
    7. Tostado-Véliz, Marcos & Jordehi, Ahmad Rezaee & Mansouri, Seyed Amir & Jurado, Francisco, 2023. "A two-stage IGDT-stochastic model for optimal scheduling of energy communities with intelligent parking lots," Energy, Elsevier, vol. 263(PD).

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