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Optimal operation of heat source and air conditioning system with thermal storage tank using nonlinear programming

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  • Ono, Hitoi
  • Ohtani, Yuichi
  • Matsuo, Minoru
  • Yamaguchi, Toru
  • Yokoyama, Ryohei

Abstract

In this paper, we consider the optimal operations of a thermal system for heat source and air conditioning system with a thermal storage tank using nonlinear programming. Firstly, we develop the mathematical model of the system components by applying the energy and mass balance principles. Secondly, the static balance of the system model is validated by the operational data. Thirdly, by applying the nonlinear programming method, IPOPT (Interior Point OPTimizer), to the mathematical model, we show the optimal operations of a thermal system under variable conditions of chilled water temperature, such as the number of person, heat generating equipment, outdoor and indoor air conditions. Finally, dynamic simulation results showed that, the variable set points of the chilled water temperature for thermal storage tank have an effect on reducing the running cost of a day.

Suggested Citation

  • Ono, Hitoi & Ohtani, Yuichi & Matsuo, Minoru & Yamaguchi, Toru & Yokoyama, Ryohei, 2021. "Optimal operation of heat source and air conditioning system with thermal storage tank using nonlinear programming," Energy, Elsevier, vol. 222(C).
    • Handle: RePEc:eee:energy:v:222:y:2021:i:c:s0360544221001857
    DOI: 10.1016/j.energy.2021.119936
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    References listed on IDEAS

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    1. Huang, Yanjun & Khajepour, Amir & Ding, Haitao & Bagheri, Farshid & Bahrami, Majid, 2017. "An energy-saving set-point optimizer with a sliding mode controller for automotive air-conditioning/refrigeration systems," Applied Energy, Elsevier, vol. 188(C), pages 576-585.
    2. Ma, Zhenjun & Wang, Shengwei, 2011. "Supervisory and optimal control of central chiller plants using simplified adaptive models and genetic algorithm," Applied Energy, Elsevier, vol. 88(1), pages 198-211, January.
    3. Homod, Raad Z., 2018. "Analysis and optimization of HVAC control systems based on energy and performance considerations for smart buildings," Renewable Energy, Elsevier, vol. 126(C), pages 49-64.
    4. Wei, Xiupeng & Xu, Guanglin & Kusiak, Andrew, 2014. "Modeling and optimization of a chiller plant," Energy, Elsevier, vol. 73(C), pages 898-907.
    5. Thangavelu, Sundar Raj & Myat, Aung & Khambadkone, Ashwin, 2017. "Energy optimization methodology of multi-chiller plant in commercial buildings," Energy, Elsevier, vol. 123(C), pages 64-76.
    6. Ikeda, Shintaro & Choi, Wonjun & Ooka, Ryozo, 2017. "Optimization method for multiple heat source operation including ground source heat pump considering dynamic variation in ground temperature," Applied Energy, Elsevier, vol. 193(C), pages 466-478.
    7. Ashok, S. & Banerjee, R., 2003. "Optimal cool storage capacity for load management," Energy, Elsevier, vol. 28(2), pages 115-126.
    8. Soler, Mònica Subirats & Sabaté, Carles Civit & Santiago, Víctor Benito & Jabbari, Faryar, 2016. "Optimizing performance of a bank of chillers with thermal energy storage," Applied Energy, Elsevier, vol. 172(C), pages 275-285.
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    Cited by:

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    4. Zhuang, Wennan & Zhou, Suyang & Chen, Jinyi & Gu, Wei, 2024. "Operation optimization of electricity-steam coupled industrial energy system considering steam accumulator," Energy, Elsevier, vol. 289(C).

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