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Economic Dispatch with Demand Response in Smart Grid: Bargaining Model and Solutions

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  • Kai Ma

    (School of Electrical Engineering, Yanshan University, Qinhuangdao 066004, China)

  • Congshan Wang

    (School of Electrical Engineering, Yanshan University, Qinhuangdao 066004, China)

  • Jie Yang

    (School of Electrical Engineering, Yanshan University, Qinhuangdao 066004, China)

  • Qiuxia Yang

    (School of Electrical Engineering, Yanshan University, Qinhuangdao 066004, China)

  • Yazhou Yuan

    (School of Electrical Engineering, Yanshan University, Qinhuangdao 066004, China
    Key Laboratory of System Control and Information Processing, Ministry of Education, Shanghai Jiao Tong University, Shanghai 200240, China)

Abstract

This paper proposes an economic dispatch strategy for the electricity system with one generation company, multiple utility companies and multiple consumers, which participate in demand response to keep the electricity real-time balance. In the wholesale markets, multiple utility companies will commonly select a reliable agent to negotiate with the generation company on the wholesale price. It is challengeable to find a wholesale price to run the electricity market fairly and effectively. In this study, we use the multiple utility companies’ profits to denote the utility function of the agent and formulate the interaction between the agent and the generation company as a bargaining problem, where the wholesale price was enforced in the bargaining outcome. Then, the Raiffa–Kalai–Smorodinsky bargaining solution (RBS) was utilized to achieve the fair and optimal outcome. In the retail markets, the unfavorable disturbances exist in the power management and price when the consumers participate in the demand response to keep the electricity real-time balance, which motivates us to further consider the dynamic power management algorithm with the additive disturbances, and then obtain the optimal power consumption and optimal retail price. Based on the consumers’ utility maximization, we establish a price regulation model with price feedback in the electricity retail markets, and then use the iterative algorithm to solve the optimal retail price and the consumer’s optimal power consumption. Hence, the input-to-state stability condition with additive electricity measurement disturbance and price disturbance is given. Numerical results demonstrate the effectiveness of the economic dispatch strategy.

Suggested Citation

  • Kai Ma & Congshan Wang & Jie Yang & Qiuxia Yang & Yazhou Yuan, 2017. "Economic Dispatch with Demand Response in Smart Grid: Bargaining Model and Solutions," Energies, MDPI, vol. 10(8), pages 1-17, August.
  • Handle: RePEc:gam:jeners:v:10:y:2017:i:8:p:1193-:d:108061
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    References listed on IDEAS

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    Cited by:

    1. Fan, Songli & Ai, Qian & Piao, Longjian, 2018. "Bargaining-based cooperative energy trading for distribution company and demand response," Applied Energy, Elsevier, vol. 226(C), pages 469-482.
    2. Wei-Tzer Huang & Kai-Chao Yao & Ming-Ku Chen & Feng-Ying Wang & Cang-Hui Zhu & Yung-Ruei Chang & Yih-Der Lee & Yuan-Hsiang Ho, 2018. "Derivation and Application of a New Transmission Loss Formula for Power System Economic Dispatch," Energies, MDPI, vol. 11(2), pages 1-19, February.
    3. Ussama Assad & Muhammad Arshad Shehzad Hassan & Umar Farooq & Asif Kabir & Muhammad Zeeshan Khan & S. Sabahat H. Bukhari & Zain ul Abidin Jaffri & Judit Oláh & József Popp, 2022. "Smart Grid, Demand Response and Optimization: A Critical Review of Computational Methods," Energies, MDPI, vol. 15(6), pages 1-36, March.
    4. Luis Alejandro Arias & Edwin Rivas & Francisco Santamaria & Victor Hernandez, 2018. "A Review and Analysis of Trends Related to Demand Response," Energies, MDPI, vol. 11(7), pages 1-24, June.

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