Multi-Objective Optimization of Renewable Energy-Driven Desalination Systems

Environmental impacts related to increasing greenhouse gas emissions and depletion of fossil-fuel reserves and water resources are major global concerns. In this work, we introduce a new multi-objective optimization model for simultaneous synthesis of zero-emission desalination plants driven by renewable energy. The system is particularly developed for zero-liquid discharge (ZLD) desalination of high-salinity shale gas wastewater, aiming to enhance economic and environmental system performance. The mathematical model is based on a multistage superstructure, which integrates a solar assisted Rankine cycle to a multiple-effect evaporation with mechanical vapor recompression (MEE-MVR) plant. For achieving the goal of more sustainable ZLD process, we specify the discharge brine salinity near to salt saturation conditions. The model is formulated as a multi-objective multiperiod non-linear programming (NLP) problem. The model is implemented in GAMS and solved via epsilon-constraint method, through the minimization of total annualized cost and environmental impacts. The economic objective function accounts for capital cost of investment and operational expenses, while environmental criteria are quantified by the life cycle assessment (LCA)-based ReCiPe methodology. A case study is performed to demonstrate the capabilities of the developed model. The obtained set of trade-off Pareto-optimal solutions reveals that integration of renewable energy generation to ZLD desalination plants can lead to significant cost and environmental savings for shale gas industry.