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Potential of District Cooling Systems: A Case Study on Recovering Cold Energy from Liquefied Natural Gas Vaporization

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  • Alice Mugnini

    (Dipartimento di Ingegneria Industriale e Scienze Matematiche, Università Politecnica delle Marche, Via Brecce Bianche 1, 60131 Ancona, Italy)

  • Gianluca Coccia

    (Dipartimento di Ingegneria Industriale e Scienze Matematiche, Università Politecnica delle Marche, Via Brecce Bianche 1, 60131 Ancona, Italy)

  • Fabio Polonara

    (Dipartimento di Ingegneria Industriale e Scienze Matematiche, Università Politecnica delle Marche, Via Brecce Bianche 1, 60131 Ancona, Italy
    Consiglio Nazionale delle Ricerche, Istituto per le Tecnologie della Costruzione, Viale Lombardia 49, 20098 San Giuliano Milanese (MI), Italy)

  • Alessia Arteconi

    (Dipartimento di Ingegneria Industriale e Scienze Matematiche, Università Politecnica delle Marche, Via Brecce Bianche 1, 60131 Ancona, Italy)

Abstract

District cooling systems (DCSs) are networks able to distribute thermal energy, usually as chilled water, from a central source to industrial, commercial, and residential consumers, to be used for space cooling/dehumidification. As cooling demand will increase significantly in the next decades, DCSs can be seen as efficient solutions to improve sustainability. Although DCSs are considered so relevant for new city developments, there are still many technical, economic, and social issues to be overcome to let such systems to spread out. Thus, this paper aims to highlight the advantages and issues linked to the adoption of DCSs for building cooling when cold is recovered from a specific application. A case study based on liquified natural gas (LNG) cold energy recovery from the transport sector is presented. Starting from the estimation of the free cooling availability, a DCS design method is proposed and the potential energy saving is investigated. Results show that a DCS using the cold waste derived from LNG can provide a relevant amount of electricity saving (about 60%) for space cooling compared to traditional solutions, in which standard air conditioning systems are installed in every building.

Suggested Citation

  • Alice Mugnini & Gianluca Coccia & Fabio Polonara & Alessia Arteconi, 2019. "Potential of District Cooling Systems: A Case Study on Recovering Cold Energy from Liquefied Natural Gas Vaporization," Energies, MDPI, vol. 12(15), pages 1-13, August.
    • Handle: RePEc:gam:jeners:v:12:y:2019:i:15:p:3027-:d:255152
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    References listed on IDEAS

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    Cited by:

    1. Broadstock, David C. & Wang, Xiangnan, 2024. "District cooling services: A bibliometric review and topic classification of existing research," Renewable and Sustainable Energy Reviews, Elsevier, vol. 190(PB).
    2. Dereje S. Ayou & Valerie Eveloy, 2020. "Integration of Municipal Air-Conditioning, Power, and Gas Supplies Using an LNG Cold Exergy-Assisted Kalina Cycle System," Energies, MDPI, vol. 13(18), pages 1-31, September.
    3. Maytungkorn Sermsuk & Yanin Sukjai & Montri Wiboonrat & Kunlanan Kiatkittipong, 2021. "Utilising Cold Energy from Liquefied Natural Gas (LNG) to Reduce the Electricity Cost of Data Centres," Energies, MDPI, vol. 14(19), pages 1-17, October.
    4. Simon Pezzutto & Philippe Riviere & Lukas Kranzl & Andrea Zambito & Giulio Quaglini & Antonio Novelli & Marcus Hummel & Luigi Bottecchia & Eric Wilczynski, 2022. "Recent Advances in District Cooling Diffusion in the EU27+UK: An Assessment of the Market," Sustainability, MDPI, vol. 14(7), pages 1-16, March.
    5. Alice Mugnini & Gianluca Coccia & Fabio Polonara & Alessia Arteconi, 2021. "Energy Flexibility as Additional Energy Source in Multi-Energy Systems with District Cooling," Energies, MDPI, vol. 14(2), pages 1-30, January.
    6. Sermsuk, Maytungkorn & Sukjai, Yanin & Wiboonrat, Montri & Kiatkittipong, Kunlanan, 2022. "Feasibility study of a combined system of electricity generation and cooling from liquefied natural gas to reduce the electricity cost of data centres," Energy, Elsevier, vol. 254(PA).
    7. Coccia, Gianluca & Mugnini, Alice & Polonara, Fabio & Arteconi, Alessia, 2021. "Artificial-neural-network-based model predictive control to exploit energy flexibility in multi-energy systems comprising district cooling," Energy, Elsevier, vol. 222(C).
    8. Ciro Aprea & Laura Canale & Marco Dell’Isola & Giorgio Ficco & Andrea Frattolillo & Angelo Maiorino & Fabio Petruzziello, 2023. "On the Use of Ultrasonic Flowmeters for Cooling Energy Metering and Sub-Metering in Direct Expansion Systems," Energies, MDPI, vol. 16(12), pages 1-16, June.

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