Multi-objective thermo-economic optimization of Collins cycle

Many large scientific projects are emerging worldwide with the development of high energy physics nowadays. The indispensable subsystem, helium cryo-plants for such projects require extremely high energy consumption and total annual cost (TAC). In order to reduce energy consumption and TAC, multi-objective thermo-economic optimization that adopted non-dominated sorting genetic algorithm-II (NSGA-II) for helium cryo-plants is proposed in this work. As a typical helium liquefaction cycle, Collins cycle is selected as the optimization object. Both the exergetic efficiency (ηEx) and the TAC are set as objective parameters. The decision parameters, which include discharge pressure of compressor, flow fraction of expanders and effectiveness of heat exchangers, are optimized simultaneously. Linear programming technology of multidimensional analysis preference (LINMAP) is utilized as an example to select the optimal solution from the multi-objective optimization results. Compared to the maximum ηEx result, the LINMAP result reduces the TAC by 23.95% at the cost of 9.03% reduction in ηEx. In the proposed approach, eight decision parameters can be optimized simultaneously and the designed cryo-plant considers both economic and thermodynamic criteria, which is feasible for practical engineering project. Besides, alternative solution under limited investment situation is provided. •A multi-objective optimization method for Collins cycle is presented.•More reasonable solutions for real engineering application are found.•Annual cost distribution is analyzed.•Optimizations of ηEx, Csl and PCsl are proved to be equivalent.•Optimization of y is not equivalent with ηEx.