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 (eta(Ex)) 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 eta(Ex) result, the LINMAP result reduces the TAC by 23.95% at the cost of 9.03% reduction in eta(Ex). 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. (C) 2021 Elsevier Ltd. All rights reserved.

Automated summary

The study proposes a multi-objective thermo-economic optimization approach using non-dominated sorting genetic algorithm-II for helium cryo-plants, with Collins cycle as the optimization object and optimizing decision parameters including compressor discharge pressure, expander flow fraction, and heat exchanger effectiveness. The use of LINMAP technology to select optimal solutions results in reduced energy consumption and total annual cost.