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Overall chilled water system energy consumption modeling and optimization

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  • Trautman, Neal
  • Razban, Ali
  • Chen, Jie

Abstract

The emergence of increasingly affordable variable-speed drive technology has changed the approach used to control chilled water systems equipped with these drives. The purpose of this research was to develop an integrated chilled water modeling technique that can determine the optimal system setpoints and estimate the energy saving potential of chiller system. The chiller system equipped with Variable Frequency Drives (VFDs) on cooling tower fans and condenser water pumps. To accomplish the objective, physical component models of the centrifugal chiller, cooling tower and condenser water pump were established with the goal of incorporating the system’s condenser water flow rate and cooling tower fan speeds as optimization variables. Furthermore, a cooling load prediction algorithm was developed using a multiple non-linear regression model to approximate the building’s cooling load subject to a range of environmental conditions. The inputs and outputs of the individual component models were linked to estimate how adjusting the cooling tower fan and condenser water pump speed would influence the system’s comprehensive performance. The overall system model was then optimized using a generalized reduced gradient optimization algorithm to determine the potential energy savings through speed control with VFDs and to ascertain a control logic strategy for the building automation system to operate the heating and cooling system. A case-study was performed on a single chiller system at a museum and the model was calibrated according to logged data collected over four months. Results showed that for the system analyzed, the energy saving of optimizing the cooling tower fan system was found to be 12–15%, while the energy saving potential of optimizing the condenser water pump with the cooling tower fan was negligible. Additionally, comparing different cooling tower fan control strategies showed that a wet-bulb approach-based cooling tower control strategy was shown to have the highest correlation to the optimized fan speed with an R2 of 0.924.

Suggested Citation

  • Trautman, Neal & Razban, Ali & Chen, Jie, 2021. "Overall chilled water system energy consumption modeling and optimization," Applied Energy, Elsevier, vol. 299(C).
    • Handle: RePEc:eee:appene:v:299:y:2021:i:c:s0306261921005997
    DOI: 10.1016/j.apenergy.2021.117166
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    References listed on IDEAS

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    1. Marguerite Frank & Philip Wolfe, 1956. "An algorithm for quadratic programming," Naval Research Logistics Quarterly, John Wiley & Sons, vol. 3(1‐2), pages 95-110, March.
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    1. Liang, Xinbin & Zhu, Xu & Chen, Siliang & Jin, Xinqiao & Xiao, Fu & Du, Zhimin, 2023. "Physics-constrained cooperative learning-based reference models for smart management of chillers considering extrapolation scenarios," Applied Energy, Elsevier, vol. 349(C).
    2. Olszewski, Pawel, 2022. "Experimental analysis of ON/OFF and variable speed drive controlled industrial chiller towards energy efficient operation," Applied Energy, Elsevier, vol. 309(C).
    3. Lian, Kuang-Yow & Hong, Yong-Jie & Chang, Che-Wei & Su, Yu-Wei, 2022. "A novel data-driven optimal chiller loading regulator based on backward modeling approach," Applied Energy, Elsevier, vol. 327(C).
    4. Shunian Qiu & Zhenhai Li & Delong Wang & Zhengwei Li & Yinying Tao, 2022. "Active Optimization of Chilled Water Pump Running Number: Engineering Practice Validation," Sustainability, MDPI, vol. 15(1), pages 1-12, December.

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