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Optimal Chiller Loading by MOEA/D for Reducing Energy Consumption

  • Yong Wang
  • Jun-qing Li
  • Mei-xian Song
  • Li Li
  • Pei-yong Duan
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 10954)

Abstract

A modified multi-objective evolutionary algorithm based on decomposition (MOEA/D) is used to solve the optimal chiller loading (OCL) problem. In a multi-chiller system, the chillers are usually partially loaded for most of the running time. If the chillers are unreasonably managed, their consumption noticeably increases. To reduce power consumption, the partial load ratio (PLR) of each chiller must be adjusted. The system must meet the system cooling load (CL), so, it is a constrained optimization problem. This study uses a multi-objective method to solve the constrained optimization. The constraint condition is changed to a new objective, so, the problem can be solved as a multi-objective problem. Comparison with the experimental results in the literature proved the effectiveness and performance of the modified algorithm, which can be fully applied in air conditioning system operations.

Keywords

Optimal chiller loading Decomposition strategy Constrained optimization 

Notes

Acknowledgments

This research is partially supported by National Science Foundation of China under Grant 61773192, 61773246 and 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), and State Key Laboratory of Synthetical Automation for Process Industries (PAL-N201602).

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Copyright information

© Springer International Publishing AG, part of Springer Nature 2018

Authors and Affiliations

  1. 1.School of ComputerLiaocheng UniversityLiaochengChina
  2. 2.School of InformationShandong Normal UniversityJinanChina
  3. 3.China Key Laboratory of Computer Network and Information Integration, Ministry of EducationSoutheast UniversityNanjingPeople’s Republic of China
  4. 4.State Key Laboratory of Synthetical Automation for Process IndustriesNortheastern UniversityShenyangChina

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