期刊
MATHEMATICS AND COMPUTERS IN SIMULATION
卷 155, 期 -, 页码 227-243出版社
ELSEVIER SCIENCE BV
DOI: 10.1016/j.matcom.2018.04.013
关键词
Optimal chiller loading; Energy saving; Artificial fish swarm algorithm
类别
资金
- National Science Foundation of China [61773192, 61773246, 61603169, 61503170]
- Shandong Province Higher Educational Science and Technology Program [J17KZ005]
- Key Laboratory of Computer Network and Information Integration (Southeast University), Ministry of Education [K93-9-2017-02]
- State Key Laboratory of Synthetical Automation for Process Industries [PAL-N201602]
This study presents an improved artificial fish swarm algorithm (VAFSA) to solve the optimal chiller loading (OCL) problem, using minimal power consumption of chillers and cooling towers as the objective function. In the proposed algorithm, several components are developed, such as initialization method based decimal system, food concentration function, bulletin board approach, target position search mechanism, and position move method. Then, the adjustment strategy of search range of artificial fish, which combines the global search with local search, is proposed for improving the search ability of VAFSA. To testify the performance of VAFSA, three well-known case studies are tested with the comparison with other recently reported approaches. The experimental results show that VAFSA can obtain power saving compared with other approaches, and also with the competitive convergence ability. The proposed algorithm can be used as an attractive alternative method to operate air-conditioning systems. (C) 2018 International Association for Mathematics and Computers in Simulation (IMACS). Published by Elsevier B.V. All rights reserved.
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