Device Modeling Method for the Entire Process of Energy-Saving Retrofit of a Refrigeration Plant

Xuanru Xu, Lun Zhang (), Jun Chen, Qingbin Lin and Junjie Chen
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Xuanru Xu: School of Energy and Environment, Southeast University, Nanjing 210096, China
Lun Zhang: School of Energy and Environment, Southeast University, Nanjing 210096, China
Jun Chen: Architectural Design and Research Institute, Southeast University, Nanjing 210096, China
Qingbin Lin: School of Energy and Environment, Southeast University, Nanjing 210096, China
Junjie Chen: School of Energy and Environment, Southeast University, Nanjing 210096, China

Energies, 2025, vol. 18, issue 15, 1-22

Abstract: With the increasing awareness of energy consumption issues, there has been a growing emphasis on energy-saving retrofits for central air-conditioning systems that constitute a significant proportion of energy consumption in buildings. Efficient energy utilization can be achieved by optimizing the modeling of the equipment within the chiller plants of central air-conditioning systems. Traditional modeling approaches have been static and have focused on modeling within narrow time frames when a certain amount of equipment operating data has accumulated, thus prioritizing the precision of the model itself while overlooking the fact that energy-saving retrofits are a long-term process. This study proposes a modeling scheme for the equipment within chiller plants throughout the energy-saving retrofit process. Based on the differences in the amount of available operating data for the equipment and the progress of retrofit implementation, the retrofit process was divided into three stages, each employing different modeling techniques and ensuring smooth transitions between the stages. The equipment within the chiller plants is categorized into two types based on the clarity of their operating characteristics, and two modeling schemes are proposed accordingly. Based on the proposed modeling scheme, chillers and chilled-water pumps were selected to represent the two types of equipment. Real operating data from actual retrofit projects was used to model the equipment and evaluate the accuracy of the model predictions. The results indicate that the models established by the proposed modeling scheme exhibit good accuracy at each stage of the retrofit, with the coefficients of variation ( CV ) remaining below 6.88%. Furthermore, the prediction accuracy improved as the retrofitting process progressed. The modeling scheme performs better on equipment with simpler and clearer operating characteristics, with a CV as low as 0.67% during normal operation stages. This underscores the potential application of the proposed modeling scheme throughout the energy-saving retrofit process and provides a model foundation for the subsequent optimization of the refrigeration system.

Keywords: device modeling; energy-saving retrofit; incremental learning; refrigeration plant (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2025
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