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Optimizing performance of a bank of chillers with thermal energy storage

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  • Soler, Mònica Subirats
  • Sabaté, Carles Civit
  • Santiago, Víctor Benito
  • Jabbari, Faryar

Abstract

We consider the problem of electricity demand shifting for the cooling needs of a large institution, using a thermal energy storage (TES) tank. The system is comprised of a number electric chillers with varying capacity and performance, as well as a tank that can store significant amount of chilled water but not enough for the whole day. The approach outlined here selects the number of chillers, and their time of operation, to minimize the costs, primarily by shifting the demand to the overnight period for which the electricity costs are lower and, due to lower ambient temperatures, the chillers are more efficient. The main goal is to develop a reliable and fast algorithm, through solving a linear or convex optimization problem, that operates the chillers at their peak efficiency and avoids excessive start-up and shut-down of chillers.

Suggested Citation

  • 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.
    • Handle: RePEc:eee:appene:v:172:y:2016:i:c:p:275-285
    DOI: 10.1016/j.apenergy.2016.03.099
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    References listed on IDEAS

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    Cited by:

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    3. Dufour, Thomas & Hoang, Hong Minh & Oignet, Jérémy & Osswald, Véronique & Clain, Pascal & Fournaison, Laurence & Delahaye, Anthony, 2017. "Impact of pressure on the dynamic behavior of CO2 hydrate slurry in a stirred tank reactor applied to cold thermal energy storage," Applied Energy, Elsevier, vol. 204(C), pages 641-652.
    4. 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.
    5. Zou, Wenke & Sun, Yongjun & Gao, Dian-ce & Zhang, Xu, 2023. "Globally optimal control of hybrid chilled water plants integrated with small-scale thermal energy storage for energy-efficient operation," Energy, Elsevier, vol. 262(PA).
    6. 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).
    7. Ron-Hendrik Peesel & Florian Schlosser & Henning Meschede & Heiko Dunkelberg & Timothy G. Walmsley, 2019. "Optimization of Cooling Utility System with Continuous Self-Learning Performance Models," Energies, MDPI, vol. 12(10), pages 1-17, May.
    8. Fanghan Su & Zhiyuan Wang & Yue Yuan & Chengcheng Song & Kejun Zeng & Yixing Chen & Rongpeng Zhang, 2023. "Enhanced Operation of Ice Storage System for Peak Load Management in Shopping Malls across Diverse Climate Zones," Sustainability, MDPI, vol. 15(20), pages 1-23, October.
    9. Zauner, Christoph & Hengstberger, Florian & Mörzinger, Benjamin & Hofmann, Rene & Walter, Heimo, 2017. "Experimental characterization and simulation of a hybrid sensible-latent heat storage," Applied Energy, Elsevier, vol. 189(C), pages 506-519.
    10. Wunvisa Tipasri & Amnart Suksri & Karthikeyan Velmurugan & Tanakorn Wongwuttanasatian, 2022. "Energy Management for an Air Conditioning System Using a Storage Device to Reduce the On-Peak Power Consumption," Energies, MDPI, vol. 15(23), pages 1-19, November.

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