Energy Consumption Prediction and Energy-Saving Optimization Research for Series-Connected Chiller Systems

Abstract To reduce the cooling energy consumption of two series-connected chillers, this study focuses on the cooling water system of the steady high magnetic field facilities. Given the varying energy efficiency of the two chillers under different load ratios, an energy-saving optimization strategy based on an energy consumption prediction model is proposed. This strategy dynamically adjusts the outlet water temperature of the upstream chiller to redistribute the cooling load between the two units, ensuring minimal total energy consumption while maintaining safe operation. The results demonstrate that the optimization strategy achieves better energy saving under larger refrigeration temperature differentials. When the total refrigeration temperature differential is 14.2 °C (from 18.5 °C to 4.3 °C), the optimization strategy reduces energy consumption by 91 kWh each hour compared to the average distribution strategy. Under typical operating conditions, the optimization strategy can save 9800 kWh of electricity each month, demonstrating a significant improvement in energy efficiency.

Authors

Institutions

Publication Details

Journal
Journal of Thermal Science and Engineering Applications
Published
2025-10-31
DOI
https://doi.org/10.1115/1.4070280
Primary Topic
Building Energy and Comfort Optimization
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Energy Consumption Prediction and Energy-Saving Optimization Research for Series-Connected Chiller Systems

Jianguo Tang, Hongling Rao, Zhong Xu, Qiqi Wu
Journal of Thermal Science and Engineering Applications
Building Energy and Comfort Optimization
article

Energy Consumption Prediction and Energy-Saving Optimization Research for Series-Connected Chiller Systems

Jianguo Tang, Hongling Rao, Zhong Xu, Qiqi Wu
article en

Abstract

Abstract To reduce the cooling energy consumption of two series-connected chillers, this study focuses on the cooling water system of the steady high magnetic field facilities. Given the varying energy efficiency of the two chillers under different load ratios, an energy-saving optimization strategy based on an energy consumption prediction model is proposed. This strategy dynamically adjusts the outlet water temperature of the upstream chiller to redistribute the cooling load between the two units, ensuring minimal total energy consumption while maintaining safe operation. The results demonstrate that the optimization strategy achieves better energy saving under larger refrigeration temperature differentials. When the total refrigeration temperature differential is 14.2 °C (from 18.5 °C to 4.3 °C), the optimization strategy reduces energy consumption by 91 kWh each hour compared to the average distribution strategy. Under typical operating conditions, the optimization strategy can save 9800 kWh of electricity each month, demonstrating a significant improvement in energy efficiency.

Journal of Thermal Science and Engineering ApplicationsVol. 18(3)
High Magnetic Field Laboratory (CN), Anhui Institute of Information Technology (CN)
Openalex Percentile: Top 66%
Building Energy and Comfort Optimization
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.