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FCH HVAC Honeycomb Ring Network—Transition from Traditional Power Supply Systems in Existing and Revitalized Areas

Author

Listed:
  • Jan Wrana

    (Faculty of Civil Engineering and Architecture, Lublin University of Technology, Nadbystrzycka 40, 20-618 Lublin, Poland)

  • Wojciech Struzik

    (Sanitary Engineer “WAKAD”, 20-250 Lublin, Poland)

  • Katarzyna Jaromin-Gleń

    (Institute of Agrophysics, Polish Academy of Sciences, Doświadczalna 4, 20-290 Lublin, Poland)

  • Piotr Gleń

    (Faculty of Civil Engineering and Architecture, Lublin University of Technology, Nadbystrzycka 40, 20-618 Lublin, Poland)

Abstract

This paper discusses the application of a new honeycomb FCH HVAC (Free Cooling and Heating System, Heating, Ventilation, and Air Conditioning) ring network technology that reduces the primary energy consumption in existing infrastructure. The aim of the research is to evaluate the cost-environmental viability of upgrading the technical infrastructure and moving from traditional to newly designed green systems built on renewable energy sources. The results show that the energy capacity stored in groundwater is equivalent to 65% of building demand, resulting in a 60% reduction in CO 2 emissions compared to a traditional HVAC system. The solution reduces the consumption of natural resources by using renewable energy sources with horizontal heat exchangers arranged in independent ring configurations.

Suggested Citation

  • Jan Wrana & Wojciech Struzik & Katarzyna Jaromin-Gleń & Piotr Gleń, 2023. "FCH HVAC Honeycomb Ring Network—Transition from Traditional Power Supply Systems in Existing and Revitalized Areas," Energies, MDPI, vol. 16(24), pages 1-14, December.
    • Handle: RePEc:gam:jeners:v:16:y:2023:i:24:p:7965-:d:1296619
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    References listed on IDEAS

    as
    1. Steven Jige Quan & Soowon Chang & Daniel Castro-Lacouture & Thomas K Igou & Florina Dutt & Jiaqi Ding & Yongsheng Chen & Perry Pei-Ju Yang, 2022. "Planning decentralized urban renewable energy systems using algal cultivation for closed-loop and resilient communities," Environment and Planning B, , vol. 49(5), pages 1464-1488, June.
    2. Qin, Haosen & Yu, Zhen & Li, Tailu & Liu, Xueliang & Li, Li, 2023. "Energy-efficient heating control for nearly zero energy residential buildings with deep reinforcement learning," Energy, Elsevier, vol. 264(C).
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