Dynamic Optimization of Multieffect Seawater Distillation to Gain Insights into Various Feeding Patterns: Productivity, Thermodynamic, Economic, and Environmental Perspectives

Seawater desalination is consistently gaining research interest, as water scarcity looms globally. Multieffect distillation with thermal vapor compression (MED-TVC) has emerged as a promising solution to the freshwater scarcity problem. In this contribution, we put forward a way to gain physical insights into various feeding patterns of MED-TVC and identify a suitable pattern to treat saline water effectively. For this, a dynamic model for a MED-TVC with parallel cross feed (PCF) is first formulated and then validated it with data sets of two different plants showing excellent matching. This validated model is further extended for dynamic multiobjective genetic algorithm-based optimization by framing four conflicting objectives in the aspects of performance ratio (PR), second law efficiency (η_II), freshwater production cost (FWPC), and CO₂ emission. With this, we formulate the technique for order of preference by similarity to ideal solution (TOPSIS) embedded nondominated sorting genetic algorithm-II (NSGA-II). A systematic comparison is presented between the optimal performance of the three feeding patterns, namely, forward, parallel, and parallel cross feed MED-TVC operating under optimal configurations. The relative merits and demerits of each feeding pattern are discussed, and among them, the PCF comes out as the front-runner with minimum cost (FWPC) and emission level and maximum performance ratio and thermodynamic efficiency. This study provides a clear and optimal picture based on the stated objectives and properly guides to choose a suitable feeding methodology for seawater desalination in MED-TVC.