Performance optimization of a multi-effect freezing desalination system driven by LNG cold energy

Freezing desalination (FD) has gained growing attention in recent years due to its low scaling and corrosion potential and low theoretical energy demand. However, its development is constrained by limited salt removal efficiency and the substantial consumption of high-grade electrical energy for refrigeration. While LNG-driven Multi-Effect Freezing Desalination (MEFD) is widely recognized as a promising solution to these challenges, existing literature remains predominantly confined to conceptual or qualitative analyses, lacking comprehensive system-level design. To address this gap, this study proposes an engineering-oriented, system-level design for an LNG-MEFD system, grounded in experimental investigation. A series of single-effect FD experiments were conducted to quantify the influence of process variables on salt rejection, recovery rate, and stirring energy consumption. Based on the experimental data, quantitative regression models linking process variables to system performance were established. These models were innovatively integrated into a holistic MEFD system design and optimization framework. Utilizing the NSGA-II algorithm, the optimal specific energy consumption (SEC) and process parameters were predicted across various application scenarios. Results indicate that a three-effect configuration is optimal for potable water production. Under typical feedwater salinity conditions of 35 ppt, the optimized thermal and electrical SEC are 465.46 kWh_t/m³ and 1.83 kWh_e/m³, respectively. These metrics are achieved under optimal operating conditions: an effect temperature of approximately −8.2 °C, and stirring speeds of 150, 112, and 248 rpm. Overall, this work provides a valuable theoretical foundation and design basis for the practical engineering of LNG-driven MEFD systems.