Multi-objective performance optimization of ORC cycle based on improved ant colony algorithm

Rong He, Xinli Wei, Nasruddin Hassan

Research output: Contribution to journalArticle

Abstract

To solve the problem of multi-objective performance optimization based on ant colony algorithm, a multi-objective performance optimization method of ORC cycle based on an improved ant colony algorithm is proposed. Through the analysis of the ORC cycle system, the thermodynamic model of the ORC system is constructed. Based on the first law of thermodynamics and the second law of thermodynamics, the ORC system evaluation model is established in a MATLAB environment. The sensitivity analysis of the system is carried out by using the system performance evaluation index, and the optimal working parameter combination is obtained. The ant colony algorithm is used to optimize the performance of the ORC system and obtain the optimal solution. Experimental results show that the proposed multi-objective performance optimization method based on the ant colony algorithm for the ORC cycle needs a shorter optimization time and has a higher optimization efficiency.

Original languageEnglish
Pages (from-to)48-59
Number of pages12
JournalOpen Physics
Volume17
Issue number1
DOIs
Publication statusPublished - 1 Jan 2019

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cycles
optimization
thermodynamics
evaluation
sensitivity analysis

Keywords

  • Ant colony algorithm
  • Multiobjective performance optimization
  • ORC cycle

ASJC Scopus subject areas

  • Physics and Astronomy(all)

Cite this

Multi-objective performance optimization of ORC cycle based on improved ant colony algorithm. / He, Rong; Wei, Xinli; Hassan, Nasruddin.

In: Open Physics, Vol. 17, No. 1, 01.01.2019, p. 48-59.

Research output: Contribution to journalArticle

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