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Notice of retraction
Vol. 34, No. 8(3), S&M3042

Notice of retraction
Vol. 32, No. 8(2), S&M2292

Print: ISSN 0914-4935
Online: ISSN 2435-0869
Sensors and Materials
is an international peer-reviewed open access journal to provide a forum for researchers working in multidisciplinary fields of sensing technology.
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is covered by Science Citation Index Expanded (Clarivate Analytics), Scopus (Elsevier), and other databases.

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Sensors and Materials, Volume 32, Number 7(2) (2020)
Copyright(C) MYU K.K.
pp. 2387-2397
S&M2267 Research Paper of Special Issue
https://doi.org/10.18494/SAM.2020.2812
Published: July 20, 2020

Optimal Chiller Loading Using Modified Artificial Bee Colony Algorithm [PDF]

Chang-Ming Lin, Ko-Ying Tseng, and Sheng-Fuu Lin

(Received November 20, 2019; Accepted April 25, 2020)

Keywords: optimal chiller loading, artificial bee colony algorithm, energy saving

In Taipei, over 45% of the energy used in buildings is for air-conditioning systems. In particular, multiple chiller systems consume about 70% of the energy in an air-conditioning system. Consequently, optimal chiller loading (OCL) or energy saving of a building is a vital issue. In this paper, we report a newly developed heuristic algorithm to solve OCL problems. A digital flow meter and a digital meter are installed to calculate the energy efficiency of a chiller. The exploration and exploitation of chiller loading can be efficiently improved without increasing the number of iterations by adopting the proposed modified artificial bee colony (MABC) algorithm. To demonstrate the performance of the proposed algorithm, it has been analyzed in comparison with other optimization methods. The result shows that the proposed algorithm can obtain a similar or better solution than previous algorithms. Therefore, it is a promising approach for solving the OCL problem.

Corresponding author: Chang-Ming Lin


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Cite this article
Chang-Ming Lin, Ko-Ying Tseng, and Sheng-Fuu Lin, Optimal Chiller Loading Using Modified Artificial Bee Colony Algorithm, Sens. Mater., Vol. 32, No. 7, 2020, p. 2387-2397.



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