Reverse Osmosis Network Research Articles

Maintenance scheduling optimisation of Reverse Osmosis Networks (RONs) via a multistage Optimal Control reformulation

State-of-the-art approaches for membrane cleaning scheduling have focused on the Mixed-Integer Nonlinear Programming (MINLP) formulation so far, a strategy leading to a combinatorial problem that does not capture accurately the dynamic behaviour of the system. In this work, the Reverse Osmosis (RO) cleaning scheduling problem is solved using a novel approach based on the Multistage Integer Nonlinear Optimal Control Problem (MSINOCP) formulation. The approach produces an automated solution for the membrane cleaning scheduling, which also obviates the need for any form of combinatorial optimisation.Two different simulations, for 26 and 52 periods of operation (each period with a duration of one week), are carried out to illustrate the application of the proposed framework and the total cost is 1.17 and 2.48107€, respectively. The RO network configuration considers 2 stages, each with 3 individual RO modules. The results show evidently that the new proposed solution framework can solve successfully this type of problems, even for large scale configurations, long time horizons and arbitrary realistic complexity of the underlying dynamic model of the RO process considered.

Flexible design and operation of multi-stage reverse osmosis desalination process for producing different grades of water with maintenance and cleaning opportunity

The use of Reverse Osmosis (RO) process in seawater desalination to provide high-quality drinking water is progressively increased compared to thermal technologies. In this paper, multistage spiral wound RO desalination process is considered. Each stage consists of several pressure vessels (PVs) organised in parallel with membrane modules in each PV being organised in series. This allows disconnecting a set of PVs and membrane modules depending on the requirement of cleaning and maintenance. While this flexibility offers the opportunity of generating several RO configurations, we presented only four such configurations of the RO system and analysed them via simulation and optimisation. Production of different grades of water catering different needs of a city is also considered for each of these configurations. The optimisation has resulted in the optimal operating conditions, which maximises the water productivity and minimises the specific energy consumption of the proposed configurations for a given water grade in terms of salinity. For instance, the results indicate that the proposed RO networks can produce drinking water of 500 ppm salinity with a minimum specific energy consumption of 3.755 kWh/m3. The strategy offers the production of different grades of water without plant shutdown while maintaining the membrane modules throughout the year.

Performance of reverse osmosis based desalination process using spiral wound membrane: Sensitivity study of operating parameters under variable seawater conditions

Reverse Osmosis (RO) process accounts for 80% of the world desalination capacity. Apparently, there is a rapid increase of deploying the RO process in seawater desalination due to its high efficiency in removing salts at a reduced energy consumption compared to thermal desalination technologies such as MSF and MED. Among different types of membranes, spiral would membranes is one of the most used. However, there is no in-depth study on the performance of spiral wound membranes in terms of salt rejection, water quality, water recovery and specific energy consumption subject to wide range of seawater salinity, temperature, feed flowrate and pressure using a high fidelity but a realistic process model which is therefore is the focus of this study. The membrane is subjected to conditions within the manufacturer's recommendations. The outcome of this research will certainly help the designers selecting optimum RO network configuration for a large-scale desalination process.

Simultaneous Optimization of Size and Operation for Seawater Reverse Osmosis Network with Permeate Split and Interstage Permeate Split Designs

Simultaneous optimization of size and operation for the seawater reverse osmosis (RO) system is proposed through a superstructure-based mixed-integer differential-algebraic programming approach. The influences of operating conditions on the performance of pumps, RO membrane, and the properties of seawater are considered. The permeate split (PS) design, interstage permeate split (ISPS) design, and on–off model could give more operability and cost saving. For constant feed conditions, nearly constant profiles of control variables are obtained with a larger water tank. The maximum level in a water tank is an indicator to measure its buffer capacity. For the variation of temperature and time-of-use electricity price, although energy consumption can be effectively saved by one time shut off at a large water demand time period with high electricity price, not much water cost is reduced due to the increase of the plant size. Low load operation is an alternative solution. The ISPS design could balance the flux distributions inside the pressure vessel and extract more permeates with high quality; thus, the water cost and energy consumption could be reduced, compared with the interstage design (ISD) and the PS design. The uncertainties of the maximum concentration of product water and the membrane fouling factor are considered in a two-stage stochastic program. It is useful for identifying a robust optimal design and operation solutions for membrane-based seawater desalination.

MINLP Model for Reverse Osmosis Network Design under Time-Variant Operation Constraints

Reverse osmosis (RO) is a very well-established technology for water desalination. Commercial RO systems are composed of several numbers of RO passes with auxiliary equipment such as high-pressure pumps and pressure-exchanger units to facilitate the separation, and to deliver clean water. Available design models for the RO network represent mixed integer nonlinear programming (MINLP) formulations. In addition, the existing RO design MINLP models are static in nature. These models are not suitable for RO network design under time-variant constraints. In this study, a multiperiod MINLP model is detailed for the RO network design. High-level design decision variables are related to the RO network configuration and equipment sizing, which are independent of time. These decisions are modeled by discrete and continuous variables. Low-level time-variant decision variables are related to the RO network operation and modeled by continuous variables. The operation decision variables are constrained by the design variables through different time periods to satisfy water-demand constraints. In addition, several correlations are considered in this study to estimate water and RO transport properties during the separation process. Case studies are analyzed to show the application of the mathematical programming model.

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.

Reverse Osmosis Network Rigorous Design Optimization

In this work, we propose a methodology to solve a nonlinear mathematical model for the optimal design of reverse osmosis (RO) networks, which ameliorates the shortcomings of the computational performance and sometimes convergence failures of commercial software to solve the rigorous mixed integer nonlinear programming (MINLP) models. Our strategy consists of the use of a genetic algorithm to obtain initial values for a full nonlinear MINLP model. In addition, because the genetic algorithm based on the rigorous model equations is insurmountably slow, we use metamodels to reduce the mathematical complexity and considerably speed up the run. We explore the effects of the feed flow, seawater concentration, number of reverse osmosis stages, and the maximum number of membrane modules in each pressure vessel on the total annualized cost of the plant.

Performance evaluation of multi-stage and multi-pass reverse osmosis networks for the removal of N-nitrosodimethylamine -D6 (NDMA) from wastewater using model-based techniques

The removal of pollutants such as N-nitrosamine present in drinking and reuse water resources is of significant interest for health and safety professionals. Reverse osmosis (RO) is one of the most promising and efficient methodologies for removing such harmful organic compounds from wastewater. Having said this, the literature confirms that the multi-stage RO process with retentate reprocessing design has not yet achieved an effective removal of N-nitrosodimethylamine-D6 (NDMA) from wastewater. This research emphasizes on this particular challenge and aims to explore several conceptual designs of multi-stage RO processes for NDMA rejection considering model-based techniques and compute the total recovery rate and energy consumption for different configurations of retentate reprocessing techniques. In this research, the permeate reprocessing design methodology is proposed to increase the process efficiency. An extensive simulation analysis is carried out using high NDMA concentration to evaluate the performance of each configuration under similar operational conditions, thus providing a deep insight on the performance of the multi-stage RO permeate reprocessing predictive design. Furthermore, an optimisation analysis is carried out on the final design to optimise the process with a high NDMA rejection performance and the practical recovery rate by manipulating the operating conditions of the plant within specified constraints bounds. The results show a superior removal of NDMA from wastewater.

Optimal Reverse Osmosis Network Configuration for the Rejection of Dimethylphenol from Wastewater

AbstractReverse osmosis (RO) has long been recognized as an efficient separation method for treating and removing harmful pollutants such as dimethylphenol in wastewater treatment. This paper studi...

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...

Effective Synthesis and Optimization Framework for Integrated Water and Membrane Networks: A Focus on Reverse Osmosis Membranes

Strict environmental regulations and social pressures have created the need for water and energy minimization in the process industries. Therefore, this work looks at the incorporation of a detailed reverse osmosis network (RON) superstructure within a water network superstructure in order to simultaneously minimize water, energy, operation, and capital costs. The water network consists of water sources, water sinks, and RO units for the partial treatment of the contaminated water. An overall mixed-integer nonlinear programming framework is developed that simultaneously evaluates both water recycle–reuse and regeneration reuse–recycle opportunities. The solution obtained from optimization provides the optimal connections between various units in the network arrangement, size and types of RO units, booster pumps, as well as energy recovery turbines. The paper looks at four cases to highlight the importance of including a detailed regeneration network within the water network instead of the traditional “bla...

Optimization of reverse osmosis networks with split partial second pass design

This study proposes an optimal study of reverse osmosis (RO) seawater desalination system based on the split partial second pass (SPSP) design in order to fully utilize better quality and higher flux for the permeate at the front of the pressure vessel (PV). Differential equations in the membrane transport model are solved by finite difference method, which considers the longitudinal variation of the superficial velocity, the pressure and the salinity inside the PV. Superstructure optimization is adopted to determine optimal flow structure, appropriate membrane type, and operation conditions. Firstly, single product RO system has been optimized, cost breakdown and sensitive analysis reveal that membrane with large active area and high salt rejection is favored for SPSP. System recovery, pressure, and split ratio for the permeate of pass 1 should be adjusted with time in order to decrease total annualized cost. Secondly, multiple product RO system has been studied. Three-pass RO configuration with permeate re-processed and brine recycled is favored for the system with two permeate products. The optimal RO configuration with three permeate products is influenced by flow rates and required permeate concentrations. In general, SPSP could provide lower cost, lower energy consumption, and smaller system size than normal design.

Optimal operations for large-scale seawater reverse osmosis networks

Optimal operation of large-scale seawater reverse osmosis (SWRO) systems, which include multiple RO plants and storage tanks, are studied to reduce the energy cost; and at the same an effective computing method was introduced for the purpose of real time optimization. With well developed models of the RO process and storage tanks based on the first principle, the optimal operation problem is subsequently formulated in the form of differential-algebraic optimization problems (DAOPs). Simultaneous collocation method was used to transform the problem into a large-scale nonlinear programming problem, and then IPOPT solver, combined with an efficient initial-value and finite-element meshing technique, was used for fast solution. Then the optimal operation problem with different variable parameters that significantly affect the performance and the energy saving of the SWRO system were investigated through case studies. Computational results show that the optimal operation problem under different conditions can be solved with high efficiency and stability, and significant energy-saving potential can be obtained through the optimal operation proposed in this paper.

Optimal seawater reverse osmosis network design considering product water boron specifications

This paper introduces a process synthesis strategy and optimization approach that accounts for boron removal considerations in Seawater Reverse Osmosis (SWRO) network design. The overall aim is to provide an improved understating of the performance of SWRO networks when specific requirements on boron levels in the system need to be met. In theory, this work utilizes the aspects of a well-defined SWRO network synthesis problem that has already been introduced in previous work, and builds on the existing representation by incorporating a number of fundamental aspects that facilitate boron removal in the system. This primarily included the determination of appropriate pH level conditions for the various network streams involved, in addition to the incorporation of a number of RO membrane element choices to be utilized in the system. Therefore, the design options allowed for the integration of a diverse mix of viable RO membrane elements within a single network, rather than strictly relying on one membrane type for all units. This was found necessary since different categories of RO membranes certainly have altered effects on the system’s performance. Efforts directed towards investigating the effects of common operating parameters on boron rejection has been carried out by means of computer-aided membrane simulation tools, in which membrane performance in the form of boron rejection were converted to useful correlations that are then used in the optimization. A case study example involving three different seawater qualities, and correspondingly three different boron levels in each, was carried as a demonstration.

Multi-objective optimization of reverse osmosis networks by lexicographic optimization and augmented epsilon constraint method

This study proposes a multi-objective optimization (MOO) of reverse osmosis (RO) networks for seawater desalination. The membrane transport model takes into consideration of the longitudinal variation of the velocity, the pressure, and the concentration in the membrane modules. The RO network with three type energy recovery device options (pressure exchanger (PX), Hydraulic Turbocharger, and turbine) is introduced. Lexicographic optimization (for calculation of a more effective payoff table) and augmented ε-constraint method (to avoid inefficient Pareto solutions) are proposed to solve the MOO problem. A fuzzy decision maker is introduced to derive the most efficient solution among Pareto-optimal solutions. Firstly, different energy recovery option studies show that using PX is seen to be the most profitable option. Exergy analysis is used to evaluate the contribution of the equipments in energy degradation. Secondly, the proposed multi-objective framework simultaneously optimizes the total annualized cost (TAC) and energy consumption. With the increases of weighting for the main objective function: TAC, the most efficient solution moves to lower TAC direction. Finally, system recovery rate is added as the third objective function. It is reasonable to stay at the appropriate system recovery rather than to increase up to its limit and generating high energetic losses.

Optimal design of split partial second pass reverse osmosis network for desalination applications

Reverse osmosis (RO) network design problem is presented in this study for seawater desalination. The RO pressure vessel is multiple spiral wound modules connected in series. We exploit in this study the RO pressure vessel operation by considering stream property variations within the pressure vessel itself. The design problem allows extraction of high‐quality permeates from different locations along the pressure vessel length. Superstructure optimization is adopted to model the RO network in order to find: (1) optimal arrangement of the process units, (2) optimal permeate extraction locations, and (3) production of several permeate streams with different qualities. Several case studies are presented to show the applications of the proposed mathematical programming model. In general, lower treatment cost and higher permeate recovery can be achieved by allowing permeate extraction streams from the RO pressure vessels. © 2013 American Institute of Chemical Engineers AIChE J 60: 520–532, 2014

MINLP based superstructure optimization for boron removal during desalination by reverse osmosis

In this work, a model based MINLP (mixed integer nonlinear programming) optimisation framework is developed for evaluating boron rejection in a reverse osmosis (RO) desalination process. A mathematical model (for the RO process) based on solution diffusion model and thin film theory is incorporated in the optimisation framework. A superstructure of the RO network is developed which includes two passes: (a) seawater pass containing normal two-stage RO system housing seawater membrane modules and (b) the brackish water pass (BW) accommodating brackish water membrane modules. For fixed freshwater demand, the objective of this work is to demonstrate the effectiveness of the MINLP approach for analyzing and optimizing the design and operation of RO network while attaining desired limit on boron concentration in the freshwater produced. The effect of seasonal variation in seawater temperature and pH on boron removal efficiency is also discussed.

Design of reverse osmosis networks for multiple freshwater production

Reverse osmosis (RO) desalination, which produces multiple freshwater from seawater, has been studied in this work. An optimization method based on process synthesis has been applied to design the RO system. First, a simplified superstructure that contains all the feasible design for this desalination problem has been presented. In this structural representation, the stream split ratios and the logical expressions of stream mixing were employed, which can make the mathematical model easy to handle. Then, the membrane separation units employing the spiral wound reverse osmosis elements were described by using a pressure vessel model, which takes into account the pressure drop and the concentration changes in the membrane channel. The optimum design problem can be formulated as a mixedinteger non-linear programming (MINLP) problem, which minimizes the total annualized cost of the RO system. The cost equation relating the capital and operating cost to the design variables, as well as the structural variables, has been introduced in the objective function. The problem solution includes the optimal streams distribution, the optimal system structure and the operating conditions. The design method could also be used for the optimal selection of membrane element type in each stage and the optimal number of membrane elements in each pressure vessel. The effectiveness of this design methodology has been demonstrated by solving a desalination case. The comparisons with common industrial approach indicated that the integrative RO system proposed in this work is more economical, which can lead to significant capital cost and energy saving and provide an economically attractive desalination scheme.

Wastewater Minimization in Pulp and Paper Industries through Energy‐Efficient Reverse‐Osmosis Membrane Processes

AbstractFresh water consumption and wastewater management is a mandatory task to conserve water resources and to reduce wastewater discharge from chemical production processes. Such objectives have been addressed in many industrial sectors which consume large amounts of fresh water. Possibilities for reducing wastewater volumes by regeneration and recycling routes in the pulp and paper industry are analyzed. During pulp preparation and paper making processes by the Kraft pulping method a large amount of water is required to deliver the finished paper product. Reverse osmosis (RO) is applied for the analyses as an interception separation technology to reduce salt concentrations in wastewater streams for recycling purposes. The RO network synthesis problem is formulated as mixed integer nonlinear programming model which is solved using the general algebraic modeling system. A preliminary cost estimate indicates economic incentives by installation of RO units to avoid wastewater discharge and generate relatively clean water streams for inter‐plant usage.

Effective design of reverse osmosis based desalination process considering wide range of salinity and seawater temperature

The design of reverse osmosis (RO) network for desalination for a wide range of salinity and seawater temperature is considered here. We start with a flexible superstructure that contains all possible alternatives of a potential RO network and refine the network during the synthesis using model based optimization technique. The synthesis problem is posed to find out an optimal RO network which will minimize the total annualized cost consisting of capital costs (costs of sea water pre-treatment, pump, turbine and membrane modules) and operating costs (pumping energy, chemicals, maintenance and membrane replacement) while fulfilling a given fresh water demand and quality. The problem results in a mixed-integer non-linear programming (MINLP) problem due to the presence of both integer and non-integer decision variables. Outer approximation algorithm within gPROMS software is used to solve the optimization problem. The results revealed that the feed salinity and temperature have significant impact on the RO network design and operation.