Applying two-stage differential evolution for energy saving in optimal chiller loading

Chang Ming Lin*, Chun Yin Wu, Ko Ying Tseng, Chih Chiang Ku, Sheng-Fuu Lin

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

5 Scopus citations


In Taiwan, over 45% of the energy in common buildings is used for the air-conditioning system. In particular, the chiller plant consumes about 70% of the energy in air-conditioning system. The electric energy consumption of air-condition system in a clean room of semiconductor factory is about 5–10 times of that in a common building. Consequently, the optimal chiller loading in energy saving of building is a vital issue. This paper develops a new algorithm to solve optimal chiller loading (OCL) problems. The proposed two-stage differential evolution algorithm integrated the advantages of exploration (global search) in the modified binary differential evolution (MBDE) algorithm and exploitation (local search) in the real-valued differential evolution (DE) algorithm for finding the optimal solution of OCL problems. In order to show the performance of the proposed algorithm, comparison with other optimization methods has been done and analyzed. The result shows that the proposed algorithm can obtain similar or better solution in comparison to previous studies. It is a promising approach for the OCL problem.

Original languageEnglish
Article number622
Issue number4
StatePublished - 15 Feb 2019


  • Energy saving
  • Multi-chiller system
  • Optimal chiller loading
  • Two-stage differential evolution

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