EconPapers    
Economics at your fingertips  
 

Optimal Chiller Loading for Energy Conservation Using an Improved Fruit Fly Optimization Algorithm

Min-Yong Qi, Jun-Qing Li, Yu-Yan Han and Jin-Xin Dong
Additional contact information
Min-Yong Qi: College of Computer Science, Liaocheng University, Liaocheng 252059, China
Jun-Qing Li: College of Computer Science, Liaocheng University, Liaocheng 252059, China
Yu-Yan Han: College of Computer Science, Liaocheng University, Liaocheng 252059, China
Jin-Xin Dong: College of Computer Science, Liaocheng University, Liaocheng 252059, China

Energies, 2020, vol. 13, issue 15, 1-18

Abstract: In the multi-chiller of the air conditioning system, the optimal chiller loading (OCL) is an important research topic. This research is to find the appropriate partial load ratio ( PLR ) for each chiller in order to minimize the total energy consumption of the multi-chiller under the system cooling load ( CL ) requirements. However, this optimization problem has not been well studied. In this paper, in order to solve the OCL problem, we propose an improved fruit fly optimization algorithm (IFOA). A linear generation mechanism is developed to uniformly generate candidate solutions, and a new dynamic search radius method is employed to balance the local and global search ability of IFOA. To empirically evaluate the performance of the proposed IFOA, a number of comparative experiments are conducted on three well-known cases. The experimental results show that IFOA found 14 optimal values (the optimal values among all algorithms) under a total of 17 CL s in three cases, and the ratio of the optimal values found was 82.4%, which was the highest among all algorithms. In addition, the mean value of all objective functions of IFOA is smaller and the standard deviation is equal to or close to 0, which proves that the algorithm has high stability. It can be concluded that IFOA is an ideal method to solve the OCL problem.

Keywords: optimal chiller loading; energy conservation; fruit fly optimization algorithm (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2020
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

Downloads: (external link)
https://www.mdpi.com/1996-1073/13/15/3760/pdf (application/pdf)
https://www.mdpi.com/1996-1073/13/15/3760/ (text/html)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:gam:jeners:v:13:y:2020:i:15:p:3760-:d:387824

Access Statistics for this article

Energies is currently edited by Ms. Agatha Cao

More articles in Energies from MDPI
Bibliographic data for series maintained by MDPI Indexing Manager ().

 
Page updated 2025-03-19
Handle: RePEc:gam:jeners:v:13:y:2020:i:15:p:3760-:d:387824