期刊
ENERGY AND BUILDINGS
卷 161, 期 -, 页码 80-88出版社
ELSEVIER SCIENCE SA
DOI: 10.1016/j.enbuild.2017.12.020
关键词
Optimal chiller loading; Invasive weed optimization; Energy consumption
资金
- National Science Foundation of China [61773192, 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]
In this study, an improved invasive weed optimization (EIWO) algorithm is investigated to solve the optimal chiller loading (OCL) problem for minimization of the power consumption. In the proposed algorithm, several components are developed, such as decimal-based representation, reproduction approach, spatial dispersal method, and competitive selection mechanism. Then, the local search strategy for elite weed is proposed, which can improve the searching ability of the algorithm. To verify the efficiency and effectiveness of the proposed algorithm, three well-known instances based on the OCL problem in air-conditioning systems are tested with the comparison with other recently published algorithms. The experimental results show that the EIWO algorithm can find equal or better optimal solution compared with other algorithms. The convergence ability, stability and robustness are also verified after the detailed comparisons. (C) 2017 Elsevier B.V. All rights reserved.
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