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Analytical Assessment for System Peak Reduction by Demand Responsive Resources Considering Their Operational Constraints in Wholesale Electricity Market

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  • Seungmi Lee

    (GIST Institute of Integrated Technology, Gwangju Institute of Science and Technology, Gwangju 61005, Korea)

  • Jinho Kim

    (GIST Institute of Integrated Technology, Gwangju Institute of Science and Technology, Gwangju 61005, Korea)

Abstract

It has been four years since the introduction of the Demand Response (DR) market in Korea. Although the DR market has been steadily increasing resource capacity and payments for demand resources, it cannot efficiently utilize DR resources under the current domestic policy system. In addition, research on the level at which the demand resource capacity registered in the DR market contributes to the reduction of peak demand is scarce. In this article, an algorithm that calculates the annual peak demand reduction contribution is developed considering the operational characteristics of DR resources in order to utilize the demand resources at a meaningful level. Also the peak demand reduction contribution is simulated for the next 15 years based on the historical electricity demand pattern in Korea and analyze the sensitivity of policy variables that affect the contribution of peak reduction. Finally, the critical policy constraint that affects the contribution of DR resources is identified and a method is proposed to improve the peak reduction contribution of DR resources. Related departments that operate the demand market can use this research as a reference for market operations.

Suggested Citation

  • Seungmi Lee & Jinho Kim, 2018. "Analytical Assessment for System Peak Reduction by Demand Responsive Resources Considering Their Operational Constraints in Wholesale Electricity Market," Energies, MDPI, vol. 11(12), pages 1-15, November.
    • Handle: RePEc:gam:jeners:v:11:y:2018:i:12:p:3343-:d:186755
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    References listed on IDEAS

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    Cited by:

    1. Tianliang Wang & Xin Jiang & Yang Jin & Dawei Song & Meng Yang & Qingshan Zeng, 2019. "Peaking Compensation Mechanism for Thermal Units and Virtual Peaking Plants Union Promoting Curtailed Wind Power Integration," Energies, MDPI, vol. 12(17), pages 1-20, August.

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