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A Bi-level gaming programming for regional integrated energy system considering the users’ reliability incentive

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  • Chen, Biyun
  • Chen, Yanni
  • Zhou, Hengwang
  • Bai, Xiaoqing
  • Li, Bin
  • Guo, Xiaoxuan

Abstract

In the context of the regional integrated energy system, as renewable energy increases and energy coupling gets higher, the operator has more resilience and flexibility to support reliability auxiliary service. To address energy reliability resource allocation, a novel method that user reliability incentive mechanism considering user reliability demand is proposed to help optimal decision making in a market vision. Thus, users’ demand for reliability differentiation in time and space dimensions will become prominent. Accordingly, we propose a master-followers bi-level gaming model with a reliability incentive mechanism. The reliability model is also innovated in the reliability constraint; the reliability reserve margin is adjusted in real-time considering the building thermal inertia and user's status. Considering user's reliability incentive, operator dispatches economically in the upper level and obtain the reliability index. With reliability improvement delivered by the upper level, users chase their maximum energy benefits by adjusting load responds on HVAC. This is considered by building thermal inertia and formulate reliability incentives based on improvement. A case study verifies the superiority of the proposed model on the participant's economy, users’ reliability, the renewable energy accommodation capacity, and differential reliability pricing. The sensitivity for external energy price and renewable energy permeability are also analyzed.

Suggested Citation

  • Chen, Biyun & Chen, Yanni & Zhou, Hengwang & Bai, Xiaoqing & Li, Bin & Guo, Xiaoxuan, 2023. "A Bi-level gaming programming for regional integrated energy system considering the users’ reliability incentive," Reliability Engineering and System Safety, Elsevier, vol. 229(C).
    • Handle: RePEc:eee:reensy:v:229:y:2023:i:c:s0951832022004562
    DOI: 10.1016/j.ress.2022.108839
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    References listed on IDEAS

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    Cited by:

    1. Wang, Xuan & Wang, Shouxiang & Zhao, Qianyu, 2024. "Low-carbon economic scheduling of multi-energy system based on price interactive response," Energy, Elsevier, vol. 300(C).
    2. Fan, Wei & Fan, Ying & Yao, Xing & Yi, Bowen & Jiang, Dalin & Wu, Lin, 2024. "Distributed transaction optimization model of multi-integrated energy systems based on nash negotiation," Renewable Energy, Elsevier, vol. 225(C).
    3. Ren, Hongbo & Jiang, Zipei & Wu, Qiong & Li, Qifen & Lv, Hang, 2023. "Optimal planning of an economic and resilient district integrated energy system considering renewable energy uncertainty and demand response under natural disasters," Energy, Elsevier, vol. 277(C).
    4. Li, Ling-Ling & Miao, Yan & Lim, Ming K. & Sethanan, Kanchana & Tseng, Ming-Lang, 2024. "Integrated energy system for low-carbon economic operation optimization: Pareto compromise programming and master-slave game," Renewable Energy, Elsevier, vol. 222(C).

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