Certeza, L. V. R. D. T., Xiao, X., Purnama, A. R., Low, J. S. C., & Lu, W. F. (2026). Optimal integration of a H2O-LiBr absorption refrigeration system into an inter-plant heat exchange network. Energy Conversion and Management, 348, 120781. https://doi.org/10.1016/j.enconman.2025.120781
Abstract:
Hot process stream refrigeration is an energy-intensive process requiring expensive refrigeration utilities. Reducing refrigeration utility consumption can be achieved by integrating an absorption refrigeration cycle (ARC) into an inter-plant heat exchange network (HEN). In view thereof, this study focuses on the optimization and economic assessment of an inter-plant HEN integrated with a H2O-LiBr ARC system. The proposed model and economic assessment procedure have been applied to two case studies. Results from case study 1 show that, relative to simple inter-plant heat integration, inter-plant HEN-ARC integration can enable a further cost reduction of 2.8% and a 600-fold increase in the savings of the plant with refrigeration needs. For case study 2, the cost reduction and savings improvement are 8.1% and nine-fold respectively. Furthermore, payback period for inter-plant HEN-ARC integration is shown to be less than four years. Meanwhile, the use of less detailed ARC models is also demonstrated to overestimate the cost of ARC-assisted process stream refrigeration by at least a factor of two compared to using the ARC model proposed in this study. Finally, inter-plant HEN-ARC integration is shown to be highly suitable when the price of refrigeration utility is high, the maximum temperature of the intermediate heat transfer fluid exceeds the target temperatures of all integrated cold process streams, and the waste heat available for the ARC system is at least 1.43 times the total refrigeration demand. Overall, this study has demonstrated the economic viability of inter-plant HEN-ARC integration and the conditions under which such scheme is best applied.
License type:
Attribution-NonCommercial-NoDerivatives 4.0 International (CC BY-NC-ND 4.0)
Funding Info:
This research is supported by the Agency for Science, Technology, and Research (A*STAR), Singapore through the Singapore International Graduate Award.