Modeling and optimization of a chiller plant

Xiupeng Wei, Guanglin Xu, Andrew Kusiak

Research output: Contribution to journalArticlepeer-review

52 Scopus citations

Abstract

A data-driven approach is utilized to model a chiller plant that has four chillers, four cooling towers, and two chilled water storage tanks. The chillers have varying energy efficiency. Since the chiller plant model derived from data-driven approach is nonlinear and non-convex, it is not practical to solve it by using the traditional gradient-based optimization algorithm. A two-level intelligent algorithm is developed to solve the model aiming at minimizing the total cost of the chilled water plant. The proposed algorithm can effectively search the optimum under the non-convex and nonlinear situation. A simulation case is conducted and the corresponding results are discussed.

Original languageEnglish (US)
Pages (from-to)898-907
Number of pages10
JournalEnergy
Volume73
DOIs
StatePublished - Aug 14 2014

Keywords

  • Chiller plant
  • Data-driven model
  • Neural network
  • Two-level intelligent algorithm

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