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Cost Apportionment Method for Transmission and Distribution Projects Based on Multiple Apportionment Factors

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  • Yongsheng Ju

    (Development Division of State Grid Gansu Electric Power Company (Economic and Technological Research Institute), Lanzhou 730000, China)

  • Yongyan Sun

    (Development Division of State Grid Gansu Electric Power Company (Economic and Technological Research Institute), Lanzhou 730000, China)

  • Wenqin Ning

    (Development Division of State Grid Gansu Electric Power Company (Economic and Technological Research Institute), Lanzhou 730000, China)

  • Qingguo Li

    (State Grid Wuwei Electric Power Supply Company, Wuwei 733000, China)

  • Yiya Lin

    (School of Economics and Management, North China Electric Power University, Beijing 102206, China)

  • Hao Chen

    (School of Economics and Management, North China Electric Power University, Beijing 102206, China)

  • Shuxia Yang

    (School of Economics and Management, North China Electric Power University, Beijing 102206, China)

Abstract

In today’s society, sustainability has become a key theme, and utilizing renewable energy is part of sustainability. Under the high proportion of renewable energy access, the conventional grid is gradually shifting to an active and distributed structure, which makes the existing cost apportionment method of transmission and distribution projects unable to match the actual situation. Reasonable apportionment of the costs of different voltage levels is the basis for the evaluation of transmission and distribution projects and is important for the formulation of transmission and distribution tariffs, which in turn have a significant impact on the development of renewable energy. To this end, this paper takes China’s power system as the research object and firstly analyzes the impact of the activization of the grid on the cost apportionment of transmission and distribution projects and then the inadequacy of the existing cost apportionment, which only considers a single factor and part of the cost which should be apportioned downward is still borne by this voltage level, and then combines the activation and the inherent characteristics of the power grid to extract the multiple factors to be considered for cost apportionment, and at the same time takes into account the reverse direction of the power trend, and divides the cost apportionment into two scenarios. The cost sharing model of transmission and distribution projects based on multiple apportionment factors is established. Finally, the feasibility and applicability of the model are verified by the examples of linear and reticulated grids, and the cost sharing results obtained by this method and the traditional method are compared. Using this method for the cost sharing of transmission and distribution projects, lower voltage levels will share more costs, and higher voltage levels will share fewer costs. The results show that the inclusion of the factors affecting cost sharing in the case of an active grid is more in line with the development trend of the new power system; the cost apportionment method based on multiple sharing factors makes the results fairer; and the inclusion of the power trend conduction relationship in the sharing process reflects the essential attributes of the grid. This is conducive to improving the operational efficiency of the power grid and promoting the long-term sustainability of the power system.

Suggested Citation

  • Yongsheng Ju & Yongyan Sun & Wenqin Ning & Qingguo Li & Yiya Lin & Hao Chen & Shuxia Yang, 2024. "Cost Apportionment Method for Transmission and Distribution Projects Based on Multiple Apportionment Factors," Sustainability, MDPI, vol. 16(20), pages 1-17, October.
  • Handle: RePEc:gam:jsusta:v:16:y:2024:i:20:p:8844-:d:1497341
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    References listed on IDEAS

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    1. Bertoletti, Paolo, 2018. "A note on Ramsey pricing and the structure of preferences," Journal of Mathematical Economics, Elsevier, vol. 76(C), pages 45-51.
    2. Passey, Robert & Haghdadi, Navid & Bruce, Anna & MacGill, Iain, 2017. "Designing more cost reflective electricity network tariffs with demand charges," Energy Policy, Elsevier, vol. 109(C), pages 642-649.
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