Chiller Plant Operation Planning via Collaborative Neurodynamic Optimization

• Published in: IEEE transactions on systems, man, and cybernetics. Systems Vol. 53; no. 8; pp. 4623 - 4635
• Main Authors: Chen, Zhongying, Wang, Jun, Han, Qing-Long
• Format: Journal Article
• Language: English
• Published: New York IEEE 01.08.2023; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Air conditioning; air conditioning (HVAC) systems; Chiller plant; Chillers; Collaboration; collaborative neurodynamic optimization (CNO); Conservation; Cooling; Cooling loads; Global optimization; heating; HVAC; Mixed integer; Neural networks; Neurodynamics; Optimization; Poles and towers; Power consumption; Power demand; Power management; Space heating; ventilation
• ISSN: 2168-2216; 2168-2232
• DOI: 10.1109/TSMC.2023.3247633

A chiller plant is an essential part of a heating, ventilation, and air conditioning system. Chiller plant operation planning is to determine the throughput of active chillers, pumps, and fans in a chiller plant to meet cooling load demands with minimized power consumption. Existing planning methods are limited to chiller plant operation with homogeneous devices subject to constraints for the conservation of energy or with heterogeneous devices without considering the conservation of energy. In this article, a mixed-integer optimization problem is formulated for chiller plant operation planning with heterogeneous devices to minimize power consumption subject to various constraints, including the constraints for the conservation of energy. The formulated problem is reformulated as a global optimization problem and solved via collaborative neurodynamic optimization with multiple projection neural networks. Experimental results based on equipment manufacturers' specifications are elaborated to demonstrate the significantly higher performance of the proposed approach than four mainstream methods in terms of power consumption wattage.