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Distributed Optimal Day-Ahead Scheduling in a Smart Grid: A Trade-Off among Consumers, Power Suppliers, and Transmission Owners

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  • Xiong Hu
  • Zhi-Wei Liu

Abstract

To cope with the challenges due to increasing peak load, an optimal day-ahead scheduling problem for social welfare maximization is proposed, in which not only the comfort level of consumers and costs of power suppliers but also the power losses in transmission and operation costs of transmission owners are taken into account. Then this optimal day-ahead scheduling problem is reformulated and solved via the alternating direction method of multipliers (ADMM), by which fast convergence is guaranteed and the privacy of participants is ensured, in a distributed manner. Specifically, in the proposed distributed optimal day-ahead scheduling, the hourly prices for consumers are divided into hourly supply prices and hourly delivery prices, which will be updated by the independent system operator based on the hourly demand-supply situations and hourly demand-delivery situations, respectively. And the consumers, power suppliers, and transmission owners make their individual optimal day-ahead scheduling based on their individual hourly prices, hourly supply prices, and hourly delivery prices, respectively, until the hourly demand-supply balances and hourly demand-delivery balances are achieved. Effectiveness of the proposed distributed optimal day-ahead scheduling is verified by the cases studied.

Suggested Citation

  • Xiong Hu & Zhi-Wei Liu, 2017. "Distributed Optimal Day-Ahead Scheduling in a Smart Grid: A Trade-Off among Consumers, Power Suppliers, and Transmission Owners," Complexity, Hindawi, vol. 2017, pages 1-11, December.
    • Handle: RePEc:hin:complx:7398041
    DOI: 10.1155/2017/7398041
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    1. Rodrigo Verschae & Takekazu Kato & Takashi Matsuyama, 2016. "Energy Management in Prosumer Communities: A Coordinated Approach," Energies, MDPI, vol. 9(7), pages 1-27, July.
    2. Jin, Xiaolong & Mu, Yunfei & Jia, Hongjie & Wu, Jianzhong & Xu, Xiandong & Yu, Xiaodan, 2016. "Optimal day-ahead scheduling of integrated urban energy systems," Applied Energy, Elsevier, vol. 180(C), pages 1-13.
    3. Jiang, Bo & Farid, Amro M. & Youcef-Toumi, Kamal, 2015. "Demand side management in a day-ahead wholesale market: A comparison of industrial & social welfare approaches," Applied Energy, Elsevier, vol. 156(C), pages 642-654.
    4. Tsitsiklis, John N. & Xu, Yunjian, 2015. "Pricing of fluctuations in electricity markets," European Journal of Operational Research, Elsevier, vol. 246(1), pages 199-208.
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