TY - JOUR
T1 - Energy optimization methodology for a centralized cold store using a multi-temperature NH3/CO2 cascade refrigeration system
AU - Ren, Dawei
AU - Shen, Shaofeng
AU - Li, Yanpeng
AU - Feng, Yiwei
AU - Liu, Yishuang
AU - Wang, Chuang
AU - Xing, Ziwen
N1 - Publisher Copyright:
© 2026 Elsevier Ltd. All rights are reserved, including those for text and data mining, AI training, and similar technologies.
PY - 2026/11/1
Y1 - 2026/11/1
N2 - Multi-temperature cascade refrigeration systems have become the preferred choice in the cold store sector due to their excellent performance at low evaporation temperatures. Therefore, an energy management strategy tailored for a centralized cold store based on multi-temperature cascade refrigeration systems is critical. Currently, there is limited research on simultaneously optimizing intermediate temperatures, high-temperature condensing temperatures and the load sharing of parallel units in cascade systems. This necessitates the development of a comprehensive strategy combining set-point optimization with multi-compressor load sharing for cascade systems. This study proposes an energy management strategy for centralized cold store based on cascade refrigeration systems. Thermodynamic and data-driven models of the system's components were established. Furthermore, optimization algorithms were applied to optimize the load sharing of parallel compressors, intermediate temperatures, and high-temperature condensing temperatures in cascade systems to reduce overall energy consumption. Simulation results based on field data indicate that this optimization strategy significantly improves energy efficiency. The parallel compressor load sharing optimization strategy reduced power consumption by 6.1% for low-temperature compressors and 2.8% for high-temperature compressors. Building on this, further optimization of the intermediate and condensing temperatures in the cascade system reduced overall energy consumption by 14.6%.
AB - Multi-temperature cascade refrigeration systems have become the preferred choice in the cold store sector due to their excellent performance at low evaporation temperatures. Therefore, an energy management strategy tailored for a centralized cold store based on multi-temperature cascade refrigeration systems is critical. Currently, there is limited research on simultaneously optimizing intermediate temperatures, high-temperature condensing temperatures and the load sharing of parallel units in cascade systems. This necessitates the development of a comprehensive strategy combining set-point optimization with multi-compressor load sharing for cascade systems. This study proposes an energy management strategy for centralized cold store based on cascade refrigeration systems. Thermodynamic and data-driven models of the system's components were established. Furthermore, optimization algorithms were applied to optimize the load sharing of parallel compressors, intermediate temperatures, and high-temperature condensing temperatures in cascade systems to reduce overall energy consumption. Simulation results based on field data indicate that this optimization strategy significantly improves energy efficiency. The parallel compressor load sharing optimization strategy reduced power consumption by 6.1% for low-temperature compressors and 2.8% for high-temperature compressors. Building on this, further optimization of the intermediate and condensing temperatures in the cascade system reduced overall energy consumption by 14.6%.
KW - Cascade refrigeration system
KW - Centralized cold store
KW - Energy management
KW - Physics-data fusion model
UR - https://www.scopus.com/pages/publications/105051339109
U2 - 10.1016/j.energy.2026.142441
DO - 10.1016/j.energy.2026.142441
M3 - 文章
AN - SCOPUS:105051339109
SN - 0360-5442
VL - 364
JO - Energy
JF - Energy
M1 - 142441
ER -