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Nuclear energy for district cooling systems – Novel approach and its eco-environmental assessment method

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  • Saleh Abushamah, Hussein Abdulkareem
  • Skoda, Radek

Abstract

The high penetration of electric-driven cooling systems in supplying the growing space cooling needs leads to significant electricity consumption and carbon emissions in many countries. In this study, a heat-driven district cooling system implementing a nuclear heat source, namely Teplator, is proposed and evaluated compared with electric-driven district cooling. The evaluation method is from an energy planning or policy-making perspective regarding electricity consumption, carbon emissions, and economics. Heat sources, heat transmission, and absorption-based cooling plants represent the heat-driven approach. In contrast, electrical power plants, electricity transmission, and compression-based cooling plants represent the electric-driven. The developed economic method is based on specific costs and average technical parameters. The main costs of construction, fuel, O&M, carbon emission, and energy transmission are included. The proposed Scenario and four electric-driven Scenarios that use coal, gas, and nuclear-based electricity are evaluated. The base results supported by sensitivity analyses confirm the potential economic viability of the proposed system in the case of a reasonable heat transmission cost. For example, each MWc.h of cooling demand could be supplied with less cost of 34%, electricity reduction of 0.32 MWe.h, and carbon emission saving of 0.26t, compared with coal electric-based Scenario.

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  • Saleh Abushamah, Hussein Abdulkareem & Skoda, Radek, 2022. "Nuclear energy for district cooling systems – Novel approach and its eco-environmental assessment method," Energy, Elsevier, vol. 250(C).
    • Handle: RePEc:eee:energy:v:250:y:2022:i:c:s0360544222007277
    DOI: 10.1016/j.energy.2022.123824
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    References listed on IDEAS

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    2. Ahmed Al-Nini & Hamdan Haji Ya & Najib Al-Mahbashi & Hilmi Hussin, 2023. "A Review on Green Cooling: Exploring the Benefits of Sustainable Energy-Powered District Cooling with Thermal Energy Storage," Sustainability, MDPI, vol. 15(6), pages 1-18, March.
    3. Li, Jiangkuan & Lin, Meng & Li, Yankai & Wang, Xu, 2022. "Transfer learning network for nuclear power plant fault diagnosis with unlabeled data under varying operating conditions," Energy, Elsevier, vol. 254(PB).

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