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Distributed carbon-aware energy trading of virtual power plant under denial of service attacks: A passivity-based neurodynamic approach

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  • Lin, Wen-Ting
  • Chen, Guo
  • Zhou, Xiaojun

Abstract

With the popularity of distributed power generation units, traditional consumers become prosumers. Meanwhile, the emerging information and communication technology brings new opportunities to the energy trading service by providing various platforms. Thus, the energy trading problem of prosumers quickly ascends to the spotlight. Nevertheless, the personalized small-scale prosumers bring challenges of coordinated operation, supply-demand balance and carbon emission control. In this paper, based on an edge-cloud platform, a distributed carbon-aware energy trading mechanism is proposed for coordinating the prosumers within the virtual power plant. Moreover, the personalized characteristics including generation cost and the carbon emissions are handled without revealing the private information under the distributed formulation. In this way, the coordination effects of the prosumers are fully explored, and a multi-agent network is employed to achieve the supply-demand balance and the carbon emission awareness. Moreover, to deal with the denial of service attacks in the cyber layer, a passivity-based neurodynamic approach is proposed, which is resilient to denial of service attacks. A set of realistic case studies on energy trading problem under denial of service attacks are given, demonstrating the effectiveness of the proposed mechanism in coordinated operation, supply-demand balancing and carbon-awareness under denial of service attacks.

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  • Lin, Wen-Ting & Chen, Guo & Zhou, Xiaojun, 2022. "Distributed carbon-aware energy trading of virtual power plant under denial of service attacks: A passivity-based neurodynamic approach," Energy, Elsevier, vol. 257(C).
    • Handle: RePEc:eee:energy:v:257:y:2022:i:c:s0360544222016541
    DOI: 10.1016/j.energy.2022.124751
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    References listed on IDEAS

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    3. Lau, Jat-Syu & Jiang, Yihuo & Li, Ziyuan & Qian, Qian, 2023. "Stochastic trading of storage systems in short term electricity markets considering intraday demand response market," Energy, Elsevier, vol. 280(C).
    4. Wang, Zheng & Li, Chaojie & Zhou, Xiaojun & Xie, Renyou & Li, Xiangyu & Dong, Zhaoyang, 2023. "Stochastic bidding for VPPs enabled ancillary services: A case study," Applied Energy, Elsevier, vol. 352(C).

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