Chiller Plant Operation Planning via Collaborative Neurodynamic Optimization

被引:10
|
作者
Chen, Zhongying [1 ]
Wang, Jun [1 ,2 ]
Han, Qing-Long [3 ]
机构
[1] City Univ Hong Kong, Dept Comp Sci, Hong Kong, Peoples R China
[2] City Univ Hong Kong, Sch Data Sci, Hong Kong, Peoples R China
[3] Swinburne Univ Technol, Sch Sci Comp & Engn Technol, Melbourne, Vic 3122, Australia
来源
IEEE TRANSACTIONS ON SYSTEMS MAN CYBERNETICS-SYSTEMS | 2023年 / 53卷 / 08期
基金
澳大利亚研究理事会;
关键词
Optimization; Cooling; Power demand; Poles and towers; HVAC; Neurodynamics; Space heating; Chiller plant; collaborative neurodynamic optimization (CNO); heating; ventilation; and air conditioning (HVAC) systems; GLOBAL OPTIMIZATION; SYSTEM; MANAGEMENT; ALGORITHM; STRATEGY;
D O I
10.1109/TSMC.2023.3247633
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
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.
引用
收藏
页码:4623 / 4635
页数:13
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