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The techno-economic and environmental analysis of genetic algorithm (GA) optimized cold thermal energy storage (CTES) for air-conditioning applications

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  • Barthwal, Mohit
  • Dhar, Atul
  • Powar, Satvasheel

Abstract

Thermal energy storage can be employed for air conditioning system load management, i.e., load shifting and leveling, to serve the peak electricity demand for the air-conditioning system with high capacity utilization. Ice and phase change material-based thermal energy storage systems were modeled and optimized for air-conditioning applications. The mathematical modeling involved energy, exergy, environmental and economic analysis of both the systems at full and partial operating modes. The system is then optimized for a commercial building to give maximized exergy efficiency and minimized total annual investment and operating cost over five different system temperatures as decision variables. The full operating mode strategy resulted in a higher exergy efficiency for both systems, whereas partial operating mode proved to be a more economical operating strategy. The multi-objective genetic algorithm-based optimization is carried out with two different refrigerants (R134a and R717) in the vapor compression refrigeration cycle of the systems. A single system design point is then selected using a multi-criteria decision-making technique. The electricity consumption while utilizing the thermal energy storage based system was lower as compared to the conventional system for air-conditioning applications. The two modeled systems are compared based on storage media, operating strategies, and the refrigerant used.

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  • Barthwal, Mohit & Dhar, Atul & Powar, Satvasheel, 2021. "The techno-economic and environmental analysis of genetic algorithm (GA) optimized cold thermal energy storage (CTES) for air-conditioning applications," Applied Energy, Elsevier, vol. 283(C).
    • Handle: RePEc:eee:appene:v:283:y:2021:i:c:s0306261920316445
    DOI: 10.1016/j.apenergy.2020.116253
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    2. Morales Sandoval, Daniel A. & Saikia, Pranaynil & De la Cruz-Loredo, Ivan & Zhou, Yue & Ugalde-Loo, Carlos E. & Bastida, Héctor & Abeysekera, Muditha, 2023. "A framework for the assessment of optimal and cost-effective energy decarbonisation pathways of a UK-based healthcare facility11The short version of the paper was presented at ICAE2022, Bochum, German," Applied Energy, Elsevier, vol. 352(C).
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    4. Gohar Gholamibozanjani & Mohammed Farid, 2021. "A Critical Review on the Control Strategies Applied to PCM-Enhanced Buildings," Energies, MDPI, vol. 14(7), pages 1-39, March.
    5. Behzadi, Amirmohammad & Holmberg, Sture & Duwig, Christophe & Haghighat, Fariborz & Ooka, Ryozo & Sadrizadeh, Sasan, 2022. "Smart design and control of thermal energy storage in low-temperature heating and high-temperature cooling systems: A comprehensive review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 166(C).
    6. Xiong, Chengyan & Meng, Qinglong & Wei, Ying'an & Luo, Huilong & Lei, Yu & Liu, Jiao & Yan, Xiuying, 2023. "A demand response method for an active thermal energy storage air-conditioning system using improved transactive control: On-site experiments," Applied Energy, Elsevier, vol. 339(C).
    7. Liu, Zichu & Quan, Zhenhua & Zhang, Nan & Wang, Yubo & Yang, Mingguang & Zhao, Yaohua, 2023. "Energy and exergy analysis of a novel direct-expansion ice thermal storage system based on three-fluid heat exchanger module," Applied Energy, Elsevier, vol. 330(PB).
    8. Ahn, Jae Hwan & Kim, Hoon & Jeon, Yongseok & Kwon, Ki Hyun, 2022. "Performance characteristics of mobile cooling system utilizing ice thermal energy storage with direct contact discharging for a refrigerated truck," Applied Energy, Elsevier, vol. 308(C).
    9. Ahn, Jae Hwan & Kim, Hoon & Kim, Jong Hoon & Kim, Ji Young, 2023. "Evaporative cooling performance characteristics in ice thermal energy storage with direct contact discharging for food cold storage," Applied Energy, Elsevier, vol. 330(PA).
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