Desalination Networks Research Articles

Optimization techniques for coupling renewable/hybrid energy options with desalination systems for carbon footprint reduction

In light of the global concerns for increased greenhouse gas (GHG) emissions, the industrial market is shifting towards more environmentally friendly processes, to meet strict emission standards. Although many studies have addressed the problem of carbon footprint reduction in desalination processes through the replacement of standard fossil fuel options with renewable energy sources, to date, none of these assessment methods have captured the effects of imposing different carbon reduction targets on the optimal design of desalination systems, and their respective energy sources. This paper proposes an optimization-based technique for the design of cost-effective desalination networks, integrated with renewable energy sources, subject to different carbon reduction targets. The presented methodology is capable of identifying optimum configurations for an integrated system that combines desalination options with renewable/hybrid energy technologies, whilst ultimately satisfying the water and energy demand that is required from the entire system. The importance of this approach lies in its ability to guide decision-making activities for such networks. A Mixed Integer Nonlinear Program (MINLP) has been proposed, which ultimately allows for the selection of the best mix between desalination technologies, and associated energy sources, based on a required carbon emission target. The proposed model has been illustrated using a case study, and the sensitivity of attained designs has been studied with respect to a number of key operating parameters.

Exergo-economic analysis and multi-objective optimization of seawater reverse osmosis desalination networks

We present a multi-objective analysis of the optimization of seawater reverse osmosis (RO) desalination systems, considering economic, power requirement, and exergo-economic factors. Exergy flow for each stream and exergy destruction for each equipment in the RO network is included in the model. The exergo-economic unit cost (EUC) for the final product is considered as an objective function. An enhanced version of the augmented epsilon constraint method, AUGMECON2, is utilized to solve the multi-objective optimization problem, which allows for lexicographic optimization for other objectives if alternative optimum solutions exist. Redundant iterations are avoided through the use of the bypass coefficient. Results show that the Pareto solutions for permeate split design are located below the normal design. Fixed cost dominates the exergo-economic unit cost. The power cost has the greatest share of water cost, while pass 1 has the greatest share of exergy destruction. The throttling valves and blending of different salinity streams (final product mixer and first pressurization stage mixer) could cause non-negligible exergy destruction. The fixed cost for each equipment, exergy rate, and EUC for each flow rate are analyzed, in order to provide insights into the system.

Optimal Multiscale Capacity Planning in Seawater Desalination Systems

The increasing demands for water and the dwindling resources of fresh water create a critical need for continually enhancing desalination capacities. This poses a challenge in distressed desalination network, with incessant water demand growth as the conventional approach of undertaking large expansion projects can lead to low utilization and, hence, low capital productivity. In addition to the option of retrofitting existing desalination units or installing additional grassroots units, there is an opportunity to include emerging modular desalination technologies. This paper develops the optimization framework for the capacity planning in distressed desalination networks considering the integration of conventional plants and emerging modular technologies, such as membrane distillation (MD), as a viable option for capacity expansion. The developed framework addresses the multiscale nature of the synthesis problem, as unit-specific decision variables are subject to optimization, as well as the multiperiod capacity planning of the system. A superstructure representation and optimization formulation are introduced to simultaneously optimize the staging and sizing of desalination units, as well as design and operating variables in the desalination network over a planning horizon. Additionally, a special case for multiperiod capacity planning in multiple effect distillation (MED) desalination systems is presented. An optimization approach is proposed to solve the mixed-integer nonlinear programming (MINLP) optimization problem, starting with the construction of a project-window interval, pre-optimization screening, modeling of screened configurations, intra-process design variables optimization, and finally, multiperiod flowsheet synthesis. A case study is solved to illustrate the usefulness of the proposed approach.

Availability and reliability analysis of integrated reverse osmosis – forward osmosis desalination network

Availability and reliability analysis of integrated reverse osmosis – forward osmosis desalination network

Desalination network model driven decision support system: A case study of Saudi Arabia

This study aims to develop a network model driven platform that supports decision-makers to make well-informed decisions for the efficient water supplies, taking Saudi Arabia as a case study. The water/energy network analysis should be able to identify optimal locations for sustainable desalination infrastructure investments, accounting for the existing assets and the current investment plans. The geographical aspect of individual resource production and distribution can be quantitatively handled by a graph-theoretic approach. This study employs a new multicommodity network flow model called the INFINIT (interdependent network flows with induced internal transformation) model, which enables to address water-energy nexus issues and to optimize the flow of multiple resources as well as placement of new water/energy facilities at the individual facility level. The INFINIT model in this study formulates and solves mixed-integer linear programming (MILP) problems to minimize the designated multi-objective functions of the total cost and CO2 emission. As a result of optimization, the Pareto-optimal solutions with different network flow topology and the downselected potential locations for new facilities are obtained. To effectively visualize alternative design and policy scenarios, two ways of visualization of the results are developed: a MATLAB-based graphical user interface and tabletop 3D map projection.

Optimization of Seawater Reverse Osmosis Desalination Networks with Permeate Split Design Considering Boron Removal

Increasingly strict constraints on the boron concentration for safe drinking and irrigation water present a tremendous challenge for the design of seawater reverse osmosis (RO) desalination systems. This work presents an optimization study of a seawater reverse osmosis RO network with permeate split (PS) design under boron concentration restrictions. Front part permeates with better quality and higher flux are sent directly to the product, and back part permeates are reprocessed in pass 2 with high pH value. The irreversible thermodynamic model is employed to describe the membrane transport behavior of boron. Constraints for the system flow and operation conditions are added to guarantee safe operating of the RO system. Both single-product and two-product RO systems are optimized for different types of feed seawater. Results show that the PS design is mainly dominated by the boron constraints, while the system recovery is mainly controlled by the feed salt concentration. Due to the upper bound of pH for p...

Environmental and economic performance assessment of desalination supply chain

The interest in desalination has been growing steadily for the recent decades due to the global increased demand for fresh water. Viewing the desalination network as a supply chain permits decision makers to evaluate the performance of desalination processes end to end. However, there are few articles considered evaluating the desalination supply chain as a whole. Thus, the purpose of this study is to develop performance measurement criteria and metrics that is designed to evaluate the efficiency of desalination supply chain concerning the economic and environmental factors. Different desalination and supply chain performance measures related to economic, and environmental perspective have been reviewed. The performance measures and metrics have been further refined by a panel of experts using Delphi technique. By adopting the analytic hierarchy process technique, a weight factor has been assigned to each perspective and metric according to its significant in desalination supply chain. It is believed that both academics and practitioners would benefit from the framework developed. Finally, it must be realized that desalination is one part of the solution. Only with a synergistic approach involving desalination, water management, consumption reduction and water reuse could efficiently solve the water demand challenge in future.

Synthesis of reverse osmosis desalination network under boron specifications

Recent regulations regarding water quality motivated research in reverse osmosis (RO) technology for water desalination especially under boron restrictions. Boron control in the permeate products by reverse osmosis technology comprises several mitigation options which impose capital and operation costs. In our study, we investigate the design of RO system under the design concept of split partial second pass reverse osmosis (SPSPRO) in order to allow extraction of permeate streams along the RO pressure vessels. The design approach is based on superstructure optimization which allows the identification of optimal process layout and optimal operation conditions of the process units. pH adjustment of the network streams is also included in the model to control boron species distribution during the separation process. A mixed integer nonlinear program (MINLP) model is subsequently formulated based on the superstructure representation. The mathematical programming formulation is demonstrated on a case study to show the application of the mathematical programming model. The results show lower treatment cost through the proposed mathematical programming model.

Optimal SWRO desalination network synthesis using multiple water quality parameters

This work introduces a systematic process synthesis and optimization approach that takes into consideration multiple water quality parameters in SWRO desalination network synthesis. Accounting for the multiple component feed water nature is particularly essential to gain insights into the distribution of components across the permeate and concentrate streams of the network, which is an important aspect of process performance. Building upon our previously developed synthesis representation and optimization scheme, we incorporate process models that are capable of addressing the multi-component nature of the problem. Analytical relations in terms of salt rejection capacities of individual ions, are developed to describe the performance of commercially available membrane elements. The designs are developed to maximize a detailed economic objective function so as to more closely resemble the costing for a commercial plant. We illustrate the approach using a case study numerical example involving four different feed water qualities with salinities ranging from 35,000 to 50,000ppm.

A Novel Approach for Targeting and Optimal Design of Efficient Seawater Reverse Osmosis Desalination Networks

Seawater reverse osmosis (SWRO) desalination processes are widely used. The optimal design of such systems resembles a network synthesis problem and has been addressed using superstructure optimization approaches. However, to date these approaches suffer from a limited ability to identify structurally distinct design alternatives, despite requiring significant computational times to determine globally optimal solutions, even for simple cases involving superstructures of only two membrane units. Moreover, existing approaches do not adequately take into consideration water quality information to keep the optimization problems solvable within reasonable times. However, SWRO design strongly depends upon the quality of the feed water and the product water specifications. This casts doubt about the relevance of the results obtained from current superstructure optimization approaches. This paper introduces a novel approach to optimal SWRO design that addresses the major shortcomings of previous approaches. We introduce a novel SWRO synthesis approach, based on the coordinated use of process superstructure representations and global optimization. The approach determines globally optimal solutions to the SWRO network synthesis problems from optimization of full superstructures. It further supports design engineers with a better understanding of the design space and trade-offs between complexity and efficiency. This is achieved through reduced superstructures of distinct design classes. The approach takes into consideration all relevant process conditions and constraints typically associated with SWRO systems. Thermodynamic insights have led to lean superstructure representations throughout which can be solved within short computational times. In contrast to previous approaches that consider sea water to consist of two components only, i.e. “water” and “salt (TDS)”, our superstructure models account for detailed water quality information to ensure practicality. The models capture the performance of the most commonly used membrane elements, as predicted by commercially used simulators including ROSA (Dow) and IMSDesign (Hydranautics) and allow tracing of individual components throughout the system. A detailed economic assessment captures all the significant capital and operating costs associated in SWRO processes, including intake, pre and post treatment. The approach is illustrated using a case study involving four different seawater qualities for which design targets and optimal designs are obtained within short CPU times.