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New model of cost allocation for micro-cogeneration systems applied in multi-family buildings — with standard and new-type multi-source energy meters

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  • Walek, Tomasz T.

Abstract

The micro-cogeneration systems MCHP used in multi-family residential buildings do not allow for the proper division of costs between the owners of individual apartments, taking into account their different profiles of power and heat consumption, because of limitations resulting from current methods of cogeneration cost allocation. Moreover, the application of MCHP systems in multi-family buildings with separate ownership structures is limited to common areas of such buildings only. The new cogeneration cost allocation method and cost clearance systems presented, extend the application of micro-cogeneration systems to all multi-family communities, regardless of their scale and ownership structure. The cost clearance systems utilize standard energy meters and new-type multi-source energy meters that allow for distinction between which part of power passing through the meter comes from the grid and which from cogeneration (analogously for heat measurement). The model equally divides cogeneration operating costs between community members regardless of their different profiles of power and heat consumption, which, in turn, reduces energy prices for all community members. The number of multi-family communities in every country where MCHP application is possible shows the large-scale potential of these systems to supplement power generation in national grids and development of innovative green-promoting energy systems.

Suggested Citation

  • Walek, Tomasz T., 2023. "New model of cost allocation for micro-cogeneration systems applied in multi-family buildings — with standard and new-type multi-source energy meters," Energy, Elsevier, vol. 262(PB).
  • Handle: RePEc:eee:energy:v:262:y:2023:i:pb:s0360544222023623
    DOI: 10.1016/j.energy.2022.125480
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    References listed on IDEAS

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    Cited by:

    1. Yang, Zhaoming & Liu, Zhe & Zhou, Jing & Song, Chaofan & Xiang, Qi & He, Qian & Hu, Jingjing & Faber, Michael H. & Zio, Enrico & Li, Zhenlin & Su, Huai & Zhang, Jinjun, 2023. "A graph neural network (GNN) method for assigning gas calorific values to natural gas pipeline networks," Energy, Elsevier, vol. 278(C).
    2. Ceglia, F. & Marrasso, E. & Pallotta, G. & Roselli, C. & Sasso, M., 2023. "Assessing the influence of time-dependent power grid efficiency indicators on primary energy savings and economic incentives for high-efficiency cogeneration," Energy, Elsevier, vol. 278(PB).

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