Improved Large-Scale Process Cooling Operation through Energy Optimization

Processes

Kriti Kapoor¹  Kody M. Powell¹  Wesley J. Cole¹  Jong Suk Kim² 

[1] McKetta Department of Chemical Engineering, The University of Texas at Austin, 200 E Dean Keeton St. Stop C0400 Austin, Austin, TX 78712-1589, USA;

关键词: energy;    chiller plant;    optimization;   

DOI  :  10.3390/pr1030312

来源: mdpi

【 摘 要 】

This paper presents a study based on real plant data collected from chiller plants at the University of Texas at Austin. It highlights the advantages of operating the cooling processes based on an optimal strategy. A multi-component model is developed for the entire cooling process network. The model is used to formulate and solve a multi-period optimal chiller loading problem, posed as a mixed-integer nonlinear programming (MINLP) problem. The results showed that an average energy savings of 8.57% could be achieved using optimal chiller loading as compared to the historical energy consumption data from the plant. The scope of the optimization problem was expanded by including a chilled water thermal storage in the cooling system. The effect of optimal thermal energy storage operation on the net electric power consumption by the cooling system was studied. The results include a hypothetical scenario where the campus purchases electricity at wholesale market prices and an optimal hour-by-hour operating strategy is computed to use the thermal energy storage tank.

【 授权许可】

CC BY   
© 2013 by the authors; licensee MDPI, Basel, Switzerland.