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Shale gas has recently emerged as a promising energy source to face the increasing global demand. This paper introduces a new rigorous optimization model for the simultaneous synthesis of single and multiple-effect evaporation (SEE/MEE) systems, considering mechanical vapor recompression (MVR) and energy recovery. The proposed model has been especially developed for the desalination of high-salinity produced water from shale gas hydraulic fracturing ("fracking"). Its main objective is to enhance the system energy efficiency through the reduction of brine discharges. Therefore, the outflow brine salinity should be near to salt saturation conditions to achieve zero liquid discharge (ZLD). The multiple-effect superstructure is comprised by several effects of horizontal-tube falling film evaporation. Due to the inclusion of the electric-driven mechanical compressor, no other external energy source is needed in the SEE/MEE system. A more accurate process design is attained through the calculation of the overall heat transfer coefficients in function of the individual coefficients for the falling boiling film and vapor condensation. Additionally, the SEE/MEE-MVR model allows the estimation of the major geometrical characteristics of the evaporation system. The non-linear programming (NLP)-based model is optimized using the CONOPT solver under GAMS by the minimization of the process total annualized cost. Thermal analysis is carried out to evaluate the effects of the feed salinity and geometrical parameters on system heat transfer performance. The results highlight the ability of the developed model to rigorously design SEE/MEE-MVR systems by improving their cost-effectively and reaching ZLD conditions. ; This project has received funding from the European Union's Horizon 2020 Research and Innovation Programme under grant agreement No. 640979. The authors also acknowledge financial support from the National Council for Scientific and Technological Development of Brazil (CNPq), under process No. 233953/2014-0.

This paper introduces a new optimization model for the single and multiple-effect evaporation (SEE/MEE) systems design, including vapor recompression cycle and thermal integration. The SEE/MEE model is specially developed for shale gas flowback water desalination. A superstructure is proposed to solve the problem, comprising several evaporation effects coupled with intermediate flashing tanks that are used to enhance thermal integration by recovering condensate vapor. Multistage equipment with intercooling is used to compress the vapor formed by flashing and evaporation. The compression cycle is driven by electricity to operate on the vapor originating from the SEE/MEE system, providing all the energy needed in the process. The mathematical model is formulated as a nonlinear programming (NLP) problem optimized under GAMS software by minimizing the total annualized cost. The SEE/MEE system application for zero liquid discharge (ZLD) is investigated by allowing brine salinity discharge near to salt saturation conditions. Additionally, sensitivity analysis is carried out to evaluate the optimal process configuration and performance under distinct feed water salinity conditions. The results highlight the potential of the proposed model to cost-effectively optimize SEE/MEE systems by producing fresh water and reducing brine discharges and associated environmental impacts. ; This project has received funding from the European Union's Horizon 2020 Research and Innovation Programme under grant agreement No. 640979. The financial support provided by the National Council for Scientific and Technological Development of Brazil (CNPq), under process No. 233953/2014-0 is also gratefully acknowledged.

Sustainable and efficient desalination is required to treat the large amounts of high-salinity flowback water from shale gas extraction. Nevertheless, uncertainty associated with well data (including water flowrates and salinities) strongly hampers the process design task. In this work, we introduce a new optimization model for the synthesis of zero-liquid discharge (ZLD) desalination systems under uncertainty. The desalination system is based on multiple-effect evaporation with mechanical vapor recompression (MEE-MVR). Our main objective is energy efficiency intensification through brine discharge reduction, while accounting for distinct water feeding scenarios. For this purpose, we consider the outflow brine salinity near to salt saturation condition as a design constraint to achieve ZLD operation. In this innovative approach, uncertain parameters are mathematically modelled as a set of correlated scenarios with known probability of occurrence. The scenarios set is described by a multivariate normal distribution generated via a sampling technique with symmetric correlation matrix. The stochastic multiscenario non-linear programming (NLP) model is implemented in GAMS, and optimized by the minimization of the expected total annualized cost. An illustrative case study is carried out to evaluate the capabilities of the proposed new approach. Cumulative probability curves are constructed to assess the financial risk related to uncertain space for different standard deviations of expected mean values. Sensitivity analysis is performed to appraise optimal system performance for distinct brine salinity conditions. This methodology represents a useful tool to support decision-makers towards the selection of more robust and reliable ZLD desalination systems for the treatment of shale gas flowback water. ; This project has received funding from the European Union's Horizon 2020 Research and Innovation Programme under grant agreement No. 640979.