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Blockchain-Enabled Demand Response Scheme with Individualized Incentive Pricing Mode

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  • Zishan Guo

    (School of Electrical and Automatic Engineering, Nanjing Normal University, No. 2 Xueyuan Road, Nanjing 210097, China
    Jiangsu Provincial Engineering Laboratory of Integrated Gas and Electrical Energy, No. 2 Xueyuan Road, Nanjing 210097, China)

  • Zhenya Ji

    (School of Electrical and Automatic Engineering, Nanjing Normal University, No. 2 Xueyuan Road, Nanjing 210097, China
    Jiangsu Provincial Engineering Laboratory of Integrated Gas and Electrical Energy, No. 2 Xueyuan Road, Nanjing 210097, China)

  • Qi Wang

    (School of Electrical and Automatic Engineering, Nanjing Normal University, No. 2 Xueyuan Road, Nanjing 210097, China
    Jiangsu Provincial Engineering Laboratory of Integrated Gas and Electrical Energy, No. 2 Xueyuan Road, Nanjing 210097, China)

Abstract

Demand response (DR) can offer a wide range of advantages for electrical systems by facilitating the interaction and balance between supply and demand. However, DR always requires a central agent, giving rise to issues of security and trust. Besides this, differences in user response cost characteristics are not taken into consideration during incentive pricing, which would affect the equal participation of users in DR and increase the costs borne by the electricity retail company. In this paper, a blockchain-enabled DR scheme with an individualized incentive pricing mode is proposed. First, a blockchain-enabled DR framework is proposed to promote the secure implementation of DR. Next, a dual-incentive mechanism is designed to successfully implement the blockchain to DR, which consists of a profit-based and a contribution-based model. An individualized incentive pricing mode is adopted in the profit-based model to decrease the imbalance in response frequency of users and reduce the costs borne by the electricity retail company. Then, the Stackelberg game model is constructed and Differential Evolution (DE) is used to produce equilibrium optimal individualized incentive prices. Finally, case studies are conducted. The results demonstrate that the proposed scheme can reduce the cost borne by the electricity retail company and decrease the imbalance among users in response frequency.

Suggested Citation

  • Zishan Guo & Zhenya Ji & Qi Wang, 2020. "Blockchain-Enabled Demand Response Scheme with Individualized Incentive Pricing Mode," Energies, MDPI, vol. 13(19), pages 1-17, October.
    • Handle: RePEc:gam:jeners:v:13:y:2020:i:19:p:5213-:d:424450
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    References listed on IDEAS

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    1. Zilong Zeng & Yong Li & Yijia Cao & Yirui Zhao & Junjie Zhong & Denis Sidorov & Xiangcheng Zeng, 2020. "Blockchain Technology for Information Security of the Energy Internet: Fundamentals, Features, Strategy and Application," Energies, MDPI, vol. 13(4), pages 1-24, February.
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    Cited by:

    1. Volpato, Gabriele & Carraro, Gianluca & Cont, Marco & Danieli, Piero & Rech, Sergio & Lazzaretto, Andrea, 2022. "General guidelines for the optimal economic aggregation of prosumers in energy communities," Energy, Elsevier, vol. 258(C).
    2. Evgenia Kapassa & Marinos Themistocleous, 2022. "Blockchain Technology Applied in IoV Demand Response Management: A Systematic Literature Review," Future Internet, MDPI, vol. 14(5), pages 1-19, April.
    3. Zhenya Ji & Zishan Guo & Hao Li & Qi Wang, 2021. "Automated Scheduling Approach under Smart Contract for Remote Wind Farms with Power-to-Gas Systems in Multiple Energy Markets," Energies, MDPI, vol. 14(20), pages 1-17, October.

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