Multi-parameter optimization of cold energy recovery in cascade Rankine cycle for LNG regasification using genetic algorithm

Gene population composed of chromosomes with various process parameters as geno types was created. Randomly created and combined chromosomes were restricted to conditions without any violation of the integrity of thermodynamic modeling. The process conditions that resulted in the maximum net produced power could be found by varying the process parameters. Ethane (C2) and propane (C3) were applied and compared as working fluids. In application of a single fluid, the C2C2 cycle showed higher maximum value than the C3C3 cycle. The C2C3 cycle showed the highest power generation among all cycles. LNG at −162 °C, 100 kPa is regasified to 10 °C, 6000 kPa NG, while sea water used as heat source enters at 15 °C, 100 kPa and exits at 10 °C, 300 kPa. In the regasification of 1 kg/s LNG mass flow rate, power generation performance was 96.3 kW in the C2C3 cycle and the first law efficiency was 11.1% at this condition.