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Technical potential and cost estimates for seawater air conditioning

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  • Hunt, Julian David
  • Byers, Edward
  • Sánchez, Antonio Santos

Abstract

In tropical climates, the energy consumed by ventilation and air conditioning can exceed 50% of the total consumption of a building. Demand for cooling is rising steadily, driven mainly by growing incomes in developing economies, and is expected to also increase with climate change. Tropical, coastal areas with narrow continental shelves are good sites for the implementation of Seawater Air Conditioning (SWAC), a renewable and low CO2 emission cooling process. This paper presents the existing SWAC projects around the world and gives details on the technology. Data on ocean temperature profiles, ocean bathymetry and world surface temperature are processed with the intent of estimating the world potential of SWAC. The results present the required distance from coast to reach seawater with a temperature of 5 °C or less. This is combined with the potential demand for air conditioning, taking into account surface air temperature and a set SWAC design for cooling from 30 to 20 °C. The pipeline length, seawater depth and capacity factor are then used to estimate the costs of SWAC projects around the world. It is concluded that the locations with the highest potential for SWAC are intertropical islands and some continental locations.

Suggested Citation

  • Hunt, Julian David & Byers, Edward & Sánchez, Antonio Santos, 2019. "Technical potential and cost estimates for seawater air conditioning," Energy, Elsevier, vol. 166(C), pages 979-988.
  • Handle: RePEc:eee:energy:v:166:y:2019:i:c:p:979-988
    DOI: 10.1016/j.energy.2018.10.146
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    References listed on IDEAS

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    8. Ríos-Ocampo, J.P. & Olaya, Y. & Osorio, A. & Henao, D. & Smith, R. & Arango-Aramburo, S., 2022. "Thermal districts in Colombia: Developing a methodology to estimate the cooling potential demand," Renewable and Sustainable Energy Reviews, Elsevier, vol. 165(C).
    9. Zhou, Yuekuan & Zheng, Siqian & Hensen, Jan L.M., 2024. "Machine learning-based digital district heating/cooling with renewable integrations and advanced low-carbon transition," Renewable and Sustainable Energy Reviews, Elsevier, vol. 199(C).
    10. Hunt, Julian David & Nascimento, Andreas & Zakeri, Behnam & Barbosa, Paulo Sérgio Franco & Costalonga, Leandro, 2022. "Seawater air-conditioning and ammonia district cooling: A solution for warm coastal regions," Energy, Elsevier, vol. 254(PB).
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