Optimization of a boil-off-gas reliquefaction system for small-scale liquefied natural gas fueling stations

Boil-off-gas (BOG) yielded in a liquefied natural gas (LNG) fueling station should be recovered to protect the environment and improve its economic performance. A BOG re-liquefaction process based on the single-stage mixed refrigerant cycle (SMR) is designed for LNG fueling stations. The thermodynamic performances of the process are analyzed based on the simulation in Aspen HYSYS, and the single and multiobjective optimization of the system is conducted using genetic algorithm (GA) and non-dominated sorting genetic algorithm-II (NSGA-II) respectively. By single-objective optimizing method, the energy consumption is reduced by 11.9%, and the system exergy efficiency is increased to 38.8% comparing with the base case. Then, a series of Pareto-optimal parameters are obtained by the multi-objective optimization, and optimal of the proposed system can be determined achieving low energy consumption and relatively high heat transfer efficiency. The results indicated the NSGA-II based multi-objective optimization could be a useful method for the BOG re-liquefaction process designing.