中国邮电高校学报(英文版) ›› 2018, Vol. 25 ›› Issue (6): 7-20.doi: 10.19682/j.cnki.1005-8885.2018.1023

• Artificial Intelligence • 上一篇    下一篇

Consortium blockchains-based deep deterministic policy gradient algorithm for optimal electricity trading among households

Yang Chen   

  1. College of Electronic and Optical Engineeringand College of Microelectronics, Nanjing University of Posts and Telecommunications, Nanjing 210023, China
  • 收稿日期:2018-05-02 修回日期:2018-12-27 出版日期:2018-12-30 发布日期:2019-02-26
  • 通讯作者: Yang Chen, E-mail: 2718699214@qq.com E-mail:2718699214@qq.com
  • 作者简介:Yang Chen, E-mail: 2718699214@qq.com

Consortium blockchains-based deep deterministic policy gradient algorithm for optimal electricity trading among households

Yang Chen   

  1. College of Electronic and Optical Engineeringand College of Microelectronics, Nanjing University of Posts and Telecommunications, Nanjing 210023, China
  • Received:2018-05-02 Revised:2018-12-27 Online:2018-12-30 Published:2019-02-26
  • Contact: Yang Chen, E-mail: 2718699214@qq.com E-mail:2718699214@qq.com
  • About author:Yang Chen, E-mail: 2718699214@qq.com

摘要: To achieve higher energy utilization and lower generation cost for renewable sources ( e. g. , wind and solar energy), much work has been focused on demand response in smart grid (SG). Nonetheless, most existing studies consider energy trading with utility company which results in high energy loss from high voltage to low voltage and privacy leakage. Besides, there are relatively few researches devoted to electricity scheduling and price optimum among households without a third party. To cope with these issues, a novel deep deterministic policy gradient (DDPG)-based energy trading method with consortium blockchain (DETCB) is introduced. Firstly, in order to enhance system security, executing energy transaction among households is on the basis of consortium blockchain, which leads to not only anonymous trade but also public account. Moreover, the primary target from the aspect of the system is apparently the maximal social welfare, thus exploiting an iterative decision-making method combined with DDPG algorithm by non-profit controllers to obtain optimal trading prices and carry out optimal electricity allocation. To this end, security analysis demonstrates that DETCB contributes to creating a secure, stable and trustful environment. Furthermore, the excellent performance concerning social welfare, algorithm efficiency, and transaction energy sum is shown by numerical results.

关键词: SG, DDPG, consortium blockchain, social welfare, non-profit, security analysis

Abstract: To achieve higher energy utilization and lower generation cost for renewable sources ( e. g. , wind and solar energy), much work has been focused on demand response in smart grid (SG). Nonetheless, most existing studies consider energy trading with utility company which results in high energy loss from high voltage to low voltage and privacy leakage. Besides, there are relatively few researches devoted to electricity scheduling and price optimum among households without a third party. To cope with these issues, a novel deep deterministic policy gradient (DDPG)-based energy trading method with consortium blockchain (DETCB) is introduced. Firstly, in order to enhance system security, executing energy transaction among households is on the basis of consortium blockchain, which leads to not only anonymous trade but also public account. Moreover, the primary target from the aspect of the system is apparently the maximal social welfare, thus exploiting an iterative decision-making method combined with DDPG algorithm by non-profit controllers to obtain optimal trading prices and carry out optimal electricity allocation. To this end, security analysis demonstrates that DETCB contributes to creating a secure, stable and trustful environment. Furthermore, the excellent performance concerning social welfare, algorithm efficiency, and transaction energy sum is shown by numerical results.

Key words: SG, DDPG, consortium blockchain, social welfare, non-profit, security analysis

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