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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

    as
    1. Tan, Zhongfu & Wang, Guan & Ju, Liwei & Tan, Qingkun & Yang, Wenhai, 2017. "Application of CVaR risk aversion approach in the dynamical scheduling optimization model for virtual power plant connected with wind-photovoltaic-energy storage system with uncertainties and demand r," Energy, Elsevier, vol. 124(C), pages 198-213.
    2. Neves, Diana & Scott, Ian & Silva, Carlos A., 2020. "Peer-to-peer energy trading potential: An assessment for the residential sector under different technology and tariff availabilities," Energy, Elsevier, vol. 205(C).
    3. Djørup, Søren & Thellufsen, Jakob Zinck & Sorknæs, Peter, 2018. "The electricity market in a renewable energy system," Energy, Elsevier, vol. 162(C), pages 148-157.
    4. Zhang, Hongwei & Wang, Jinsong & Ding, Yuemin, 2019. "Blockchain-based decentralized and secure keyless signature scheme for smart grid," Energy, Elsevier, vol. 180(C), pages 955-967.
    5. Hua, Weiqi & Jiang, Jing & Sun, Hongjian & Wu, Jianzhong, 2020. "A blockchain based peer-to-peer trading framework integrating energy and carbon markets," Applied Energy, Elsevier, vol. 279(C).
    6. Thomas Morstyn & Niall Farrell & Sarah J. Darby & Malcolm D. McCulloch, 2018. "Using peer-to-peer energy-trading platforms to incentivize prosumers to form federated power plants," Nature Energy, Nature, vol. 3(2), pages 94-101, February.
    7. Licklederer, Thomas & Hamacher, Thomas & Kramer, Michael & Perić, Vedran S., 2021. "Thermohydraulic model of Smart Thermal Grids with bidirectional power flow between prosumers," Energy, Elsevier, vol. 230(C).
    8. Klein, Lurian P. & Matos, Luisa M. & Allegretti, Giovanni, 2020. "A pragmatic approach towards end-user engagement in the context of peer-to-peer energy sharing," Energy, Elsevier, vol. 205(C).
    9. Zhang, Chenghua & Wu, Jianzhong & Zhou, Yue & Cheng, Meng & Long, Chao, 2018. "Peer-to-Peer energy trading in a Microgrid," Applied Energy, Elsevier, vol. 220(C), pages 1-12.
    10. Alam, Muhammad Raisul & St-Hilaire, Marc & Kunz, Thomas, 2019. "Peer-to-peer energy trading among smart homes," Applied Energy, Elsevier, vol. 238(C), pages 1434-1443.
    11. Zhuang, Yuan & Zhu, Guodong & Gong, Zhen & Wang, Chenfang & Huang, Yuhan, 2019. "Experimental and numerical investigation of performance of an ethanol-gasoline dual-injection engine," Energy, Elsevier, vol. 186(C).
    12. Zarnikau, J. & Tsai, C.H. & Woo, C.K., 2020. "Determinants of the wholesale prices of energy and ancillary services in the U.S. Midcontinent electricity market," Energy, Elsevier, vol. 195(C).
    13. Alqahtani, Mohammed & Hu, Mengqi, 2020. "Integrated energy scheduling and routing for a network of mobile prosumers," Energy, Elsevier, vol. 200(C).
    14. Kasaei, Mohammad Javad & Gandomkar, Majid & Nikoukar, Javad, 2017. "Optimal management of renewable energy sources by virtual power plant," Renewable Energy, Elsevier, vol. 114(PB), pages 1180-1188.
    15. Hashemipour, Naser & Crespo del Granado, Pedro & Aghaei, Jamshid, 2021. "Dynamic allocation of peer-to-peer clusters in virtual local electricity markets: A marketplace for EV flexibility," Energy, Elsevier, vol. 236(C).
    16. Yu, Songyuan & Fang, Fang & Liu, Yajuan & Liu, Jizhen, 2019. "Uncertainties of virtual power plant: Problems and countermeasures," Applied Energy, Elsevier, vol. 239(C), pages 454-470.
    17. Gross, Michel & Karbasi, Babak & Reiners, Tobias & Altieri, Lisa & Wagner, Hermann-Josef & Bertsch, Valentin, 2021. "Implementing prosumers into heating networks," Energy, Elsevier, vol. 230(C).
    Full references (including those not matched with items 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).

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