The helium cryo-plant is an indispensable subsystem for the application of
low-temperature superconductors in large-scale scientific facilities.
However, it is important to note that the cryo-plant requires stable
operation and consumes a substantial amount of electrical power for its
operation. Additionally, the construction of the cryo-plant incurs
significant economic costs. To achieve the necessary cooling capacity while
reducing power consumption and ensuring stability and economic feasibility,
constrained multi-objective optimization is performed using the interior
point method in this work. The Collins cycle, which uses liquid nitrogen
precooling, is selected as the representative helium liquefaction cycle for
optimization. The discharge pressure of the compressor, flow ratio of
turbines, and effectiveness of heat exchangers are taken as decision
parameters. Two objective parameters, cycle exergy efficiency (?Ex,cycle) and
liquefaction rate (m?L), are chosen, and the wheel tip speed of turbines and
UA of heat exchangers are selected as stability and economic cost
constraints, respectively. The technique for Order of Preference by
Similarity to the Ideal Solution (TOPSIS) is utilized to select the final
optimal solution from the Pareto frontier of constrained multi-objective
optimization. Compared to the constrained optimization of ?Ex,cycle, the TOPSIS
result increases the m?L by 23.674%, but there is an 8.162% reduction in ?Ex,cycle.
Similarly, compared to the constrained optimization of m?L, the TOPSIS result
increases the ?Ex,cycle by 57.333%, but a 10.821% reduction in m?L is observed. This
approach enables the design of helium cryo-plants with considerations for
cooling capacity, exergy efficiency, economic cost, and stability.
Furthermore, the wheel tip speed and UA of heat exchangers of the solutions
in the Pareto frontier are also studied.