Seawater Reverse Osmosis Desalination Research Articles

ANN based-model for estimating the boron permeability coefficient as boric acid in SWRO desalination plants using ensemble-based machine learning

This study examines the relationship between input conditions and the prediction of boron rejection in full-scale seawater reverse osmosis (SWRO) desalination plants using ensemble-based machine learning. While reverse osmosis is the dominant desalination technology, limited research has focused on analyzing plant performance under actual operating conditions. To address this gap, we developed and implemented machine learning algorithms to forecast boron permeability coefficient values, which are indicative of boron rejection concentrations in the permeate. Our analysis utilizes data from a SWRO desalination plant in southeast Spain, examining various input variables and their influence on the prediction of these parameters. The results demonstrate that our ensemble-based machine learning approach can predict boron permeability coefficient values with a reasonable margin of error of 1 mgL−1, as evidenced by mean average error (MAE) and mean absolute percentage error (MAPE) values of 7.93·10–8 and 11.8 %, respectively. In conclusion, an innovative application of artificial intelligence algorithms in the field of water purification under real operational conditions has been introduced, thus introducing valuable insights into the use of machine learning algorithms for forecasting boron rejection concentrations in full-scale SWRO desalination plants. The findings lay the foundation for future researches exploring automated and deep-learning methods in water purification.

A comprehensive evaluation of the temporal and spatial fouling characteristics of RO membranes in a full-scale seawater desalination plant

The fouling of seawater reverse osmosis (SWRO) membranes remains a persistent challenge in desalination. Previous research has focused mainly on fouling separately; however, organic, inorganic, and biofouling can coexist and influence each other. Hence, in-depth study of the spatiotemporal changes in actual combined fouling in full-scale seawater desalination will provide more effective information for fouling investigation and control. In this study, we monitored (i) the operational performance of a full-scale desalination plant for 7 years and (ii) the development and characterization of membrane and spacer fouling at different locations of spiral-wound membrane modules sampled after 2.5-, 3.5-, and 7-year operation. The findings showed that (i) operational performance indicators declined with time (normalized flux 40 % reduction, salt rejection 2 % in 7 years), with a limited effect of the 20-day cleaning frequency, (ii) fouling accumulation in the membrane module mainly occurred at the feed side of the lead module and the microbial community in these area exhibited the highest diversity, (iii) the dominant microbial OTUs belonged mainly to Proteobacteria (43–70 %), followed by Bacteroidetes (10–11 %), (iv) Phylogenetic molecular ecological networks and Spearman correlation analysis revealed that Chloroflexi (Anaerolineae) and Planctomycetes were keystone species in maintaining the community structure and biofilm maturation and significantly impacted the foulant content on the SWRO membrane, even with low abundance, and that (v) fouling accumulation was composed of polysaccharides, soluble microbial products, marine humic acid-like substances, and inorganic Ca/Fe/Mg/Si dominate the fouling layer of both the membrane and spacer. Overall, variation partitioning analysis quantitatively describes the increasing contribution of biofouling over time. Ultimately, the organic‒inorganic-biofouling interaction (70 %) significantly contributed to the overall fouling of the membrane after 7 years of operation. These results can be used to develop more targeted fouling control strategies to optimize SWRO desalination plant design and operation.

Polyelectrolyte multilayers modification of nanofiltration membranes to improve selective separation of mono- and multivalent cations in seawater brine

Nowadays, brine produced in the Reverse Osmosis (RO) seawater desalination plants is a significant and largely untapped source of critical minerals and metals, which is usually discharged into the seas as wastewater. As a front face stage in the brine mining process, nanofiltration (NF) membranes can be used to separate brine stream into monovalent and multivalent ion-rich streams. Since high separation factors are required in seawater RO brine, polyelectrolyte multilayers with Layer-by-Layer (LbL) technique were used in this study to modify commercial polyamide NF membranes and improve their performance. Two common polyelectrolytes, poly(diallyldimethylammonium chloride) (PDADMAC) and poly(sodium 4-styrenesulfonate) (PSS) were coated onto two poly-piperazine polyamide NF membranes (NF270 and Desal-5 DL). The effects of the bilayers number and the outer layer charge on membranes’ performance were studied using two crossflow filtration setups with two different membrane sizes to find the membrane with the higher monovalent/multivalent separation factor. Desal-5 DL membrane coated with 5.5 bilayers provided the highest selectivity factors for mono/multivalent cations (> 21), the highest average rejection of multivalent cations group (about 95.7%) for short-term experiments. Another interesting result was the increase in water permeance of the Desal-5 DL membrane after it was coated with 5.5 bLs (indicating more than 20% improvement in pure water permeance). In addition, the stability test with brines at 20 bar showed that this membrane was stable over an extended period of filtration (22 hours) with an even higher selectivity factor of 34 and multivalent cations rejection of 97.7% on average.

A Comparison of Power Take-Off Architectures for Wave-Powered Reverse Osmosis Desalination of Seawater with Co-Production of Electricity

Several power take-off (PTO) architectures for wave-powered reverse osmosis (RO) desalination of seawater are introduced and compared based on the annual average freshwater production and the size of the components, which strongly relate to the costs of the system. The set of architectures compared includes a novel series-type PTO architecture not previously considered. These seawater hydraulic PTO architectures are composed of a WEC-driven pump, an RO module, an intake charge pump driven by an electric motor, and a hydraulic motor driving an electric generator for electric power production. This study is performed using an efficient two-way coupled steady-state model for the average performance of the system in a given sea state, including freshwater permeate production, electric power production, and electric power consumption. A multi-objective design problem is formulated for the purposes of this comparative study, with the objectives of maximizing annual freshwater production, minimizing the displacement of the WEC-driven pump, and minimizing the installed RO membrane area. This establishes a framework for comparison in the absence of a mature techno-economic model. The requirement that the system produces enough electric power to meet its consumption is applied as a constraint on the operation of the system. The oscillating wave surge converter Oyster 1 is assumed as the WEC. Weights on performance of the system in a given sea state are based on historical data from Humboldt Bay, CA. This study finds that (1) architectures in a series configuration allow for a reduction in the WEC-driven pump size of 59–92% compared to prior work, (2) varying the displacement of the WEC-driven pump between sea conditions does not provide any significant advantage in performance, and (3) varying the active RO membrane area between sea condition offers improvements between 7% and 41% in each design objective.

Joint research aims to improve the way energy is used in desalination

Saudi Arabia's ACWA Power and Toray Industries Inc are collaborating on a project that aims to research and develop energy-saving technologies for use in seawater reverse osmosis desalination facilities.

Peroxymonosulfate based in situ chemical oxidation: An efficient strategy for mitigation of membrane fouling in real seawater reverse osmosis desalination

Persulfate based advanced oxidation processes (AOPs) is an emerging method to assist the pretreatment to prevent membrane fouling for seawater desalination. However, the present strategies which adopt activators (e.g., UV, heat, Fe) to generate kinds of free radicals, are energy-consuming and enhance the concerns of disinfection by-products (DBPs). Here, peroxymonosulfate (PMS) is adopted as a green, effective and economical pretreatment chemical for simultaneous microorganic pollutants degradation and microorganism inactivation in seawater reverse osmosis (SWRO) desalination without any external energy input. After adding into the seawater, 53% PMS could be activated by Cl- in situ to generate HClO at most with no other active species generated, which is verified by stoichiometric analysis and quenching experiments. Benefited from the residual PMS, not only could up to 89.6% of total organic carbon be removed in the real seawater, but also nearly 80% of DBPs could be degraded by simply adjusting pH from neutral to alkaline conditions. Meanwhile, all bacteria could be killed completely and hardly any regrowth appeared, which further proved the anti-fouling ability of the PMS/Cl- system. Consequently, the addition of PMS could maintain the flux for a long time in the practical SWRO application with significantly reducing the RO membrane fouling. Moreover, the operating cost of PMS is only 0.024 $/ton, which is comparable to NaClO. This study demonstrated the excellent performance of PMS in SWRO pretreatment, supplying a promising scheme in practical desalination processes.

Optimization of sustainable seawater desalination: Modeling renewable energy integration and energy storage concepts

Many arid and semi-arid regions of the world face growing freshwater scarcity, requiring increased utilization of seawater desalination to augment the existing freshwater resources. Seawater reverse osmosis (RO) is currently one of the most deployed technologies, due to its electrical energy efficiency and comparatively low costs. However, the required energy for desalination processes is often still converted from fossil sources. Given the growing demand for seawater desalination and the energy sector’s parallel decarbonization, the substitution by renewable energy sources (RES) is a critical issue. The volatility, lower availability of renewable energy, and cost for required electrical energy storage (EES) are all obstacles to the decarbonization of large-scale desalination plants and may affect production volume and water production costs negatively.This paper presents a mathematical model to determine a cost-optimal energy conversion and EES mix for the design and operation of large-scale seawater RO desalination plants. The linear program ensures satisfaction of the plant’s energetic demands. Furthermore, the model allows to investigate the general feasibility of integrating RES into large-scale desalination processes, which are examined by means of a case study while employing location-specific weather data. Different types of energy conversion technologies and the effect of EES on operating behavior, greenhouse gas emissions, and water unit costs are investigated. Specifically, the indirect storage of electrical energy via the smart management of a desalination plant’s oversized RO membranes is examined and compared to battery energy storage (BES).Results indicate that RES cannot meet an RO desalination plant’s full and constant electrical load demand without a high BES capacity, which is probably not feasible from a technical and economic point of view. The economic penalty from energy storage costs on one unit of desalinated water ranges from 3.10 $/m3 up to 5.38 $/m3. However, operating an oversized RO desalination plant intermittently could reduce the energy-related costs substantially and potentially provide a more appropriate way of adapting to a volatile supply of energy from renewable sources in order to decarbonize the desalination processes. Specific emissions of desalinated water can be reduced from 1.5 kg CO2 eq./m3 when relying mostly on combined cycle gas turbines down to 0.124 kg CO2 eq./m3 by intermittent operation and fully relying on renewable energy sources.

Pilot study of emerging low-energy seawater reverse osmosis desalination technologies for high-salinity, high-temperature, and high-turbidity seawater

The increasing impact of climate change has worsened drought conditions, leading to a surge in the demand for seawater desalination. However, current seawater reverse osmosis (SWRO) desalination technologies are not energy-efficient for handling the high-salinity, high-temperature, and high-turbidity seawater found in the Arabian Gulf. Therefore, a pilot-scale SWRO desalination plant was established to evaluate the new desalination technologies. The pilot plant tested high-performance SWRO membranes, meshed tube filtration (MTF) as a low-energy pretreatment for the high turbidity induced by algal blooms, and membrane capacitive deionization (MCDI) to improve permeate quality. The high-performance SWRO membrane demonstrated exceptional salt rejection and produced permeate quality in the range of 250–455 mg/L from the feed with salinities of 47,500–53,500 mg/L. MTF was effective in controlling turbidity, and the energy consumption was reduced by 77 % compared to the existing pretreatment process. Furthermore, MCDI exhibited similar levels of energy efficiency as brackish water reverse osmosis and may have the potential for future deployment by enhancing process development. Based on the pilot plant results, it is expected that a 100,000–200,000 m3/d SWRO desalination plant will have a specific energy consumption of 3.11–3.13 kWh/m3 for final product water quality at or below 200 mg/L.

Raman spectroscopy for real-time concurrent detection of multiple scalants on RO membranes

In-situ monitoring techniques of reverse osmosis (RO) desalination systems, particularly those with chemical sensing capabilities, can provide the means for better understanding important scaling mechanisms as well as early scaling detection. In this work, both calcium sulfate and calcium carbonate scaling on RO membranes were detected concurrently in real time using Raman spectroscopy to provide a unique chemical fingerprint. Two different sampling methodologies (manual and automated) were employed, and their performance was evaluated by comparing the Raman detection times to concurrent values of flux decline. The manual sampling strategy resulted in the detection of calcium sulfate and calcium carbonate at mean permeate flux declines of 13 ± 10 % and 22 ± 3 %, respectively. The automated sampling strategy provided better performance, with detection of calcium sulfate and calcium carbonate at mean flux declines of 8 ± 5 % and 4 ± 3 %, respectively. The increased sensitivity and decreased variability of the automated sampling strategy provided valuable preliminary insights for the selection of optimized sampling strategies. The ability to identify the chemical composition of different scaling crystals including their polymorphs is an important step toward better understanding of the crystallization pathways of multi-component feed streams used in seawater and brackish water RO desalination.

A theoretical analysis on upgrading desalination plants with low-salt-rejection reverse osmosis

Brackish water/seawater reverse osmosis (RO) desalination is a key solution to global freshwater scarcity. However, the water recovery (Rw) in conventional RO desalination plants is limited by the operating pressure (∆P). As a novel staged RO technology, low-salt-rejection RO (LSRRO) can potentially enhance the Rw in the desalination plants. In this study, we perform process modeling and techno-economic analysis to evaluate the viability of upgrading current RO desalination plants with LSRRO. Based on the results from process modeling, in typical brackish water RO (BWRO) and seawater RO (SWRO) desalination plants, adding an LSRRO stage can effectively enhance the Rw by 21 and 53 %, respectively, and the energy efficiencies are not compromised with the enhanced Rw. From techno-economic analysis, upgrading RO desalination plant with LSRRO is highly viable. Specifically, after adding an LSRRO stage in a BWRO plant, the Rw can be enhanced from 71 to 81 % without notably increasing the levelized cost of water (LCOW), and adding an LSRRO stage in the SWRO plant with zero brine discharge can reduce the LCOW by 30 %. The findings in our study highlight the vast potential of adopting LSRRO in brackish water/seawater desalination plants, and shed lights on the design of future desalination plants.

Forecasting of Permeate Conductivity using MLR and ANN Methods of Boujdour Seawater Reverse Osmosis Desalination Plant

Background: For many years, seawater desalination technique has been operational to deal with water scarcity. In Boujdour region, located near the Atlantic Ocean southwest of Morocco, most water drinking is produced by a reverse osmosis seawater desalination plant. The permeate conductivity prediction is used to evaluate the performance of desalination plants. Objective: The present paper focuses on the modeling and comparison of the Artificial Neural Network (ANN) and Multiple Linear Regression (MLR) for the prediction of permeate conductivity for a one-year period. Methods: Six input variables are considered, including turbidity, temperature, pH, feed conductivity, feed flow, and transmembrane pressure (TMP). Firstly, the MLR identifies the most important variables influencing the permeate conductivity with the aim of developing a regression model for the dependent and independent parameters. Secondly, the ANN method is examined to analyze the performance of desalination plant. A study of the effect of the number of neurons and the number of hidden layers on the efficiency of the neural network has been made. Results and Conclusion: Results confirm that the MLR and ANN models forecast the permeate conductivity with a suitable coordination coefficient of the real and predicted values. ANN model has been successfully tested for reliability with a correlation coefficient R2 of 99.097% and a mean square error (MSE) of 0.002607.

D (+)-Glucosamine (DGA) based polyesteramide TFC NF membrane for the pretreatment of reverse osmosis seawater desalination

Reverse osmosis is an effective seawater desalination way extending the available sources of fresh water, but challenged by the gypsum scaling. Herein, D (+)-glucosamine (DGA) was rationally selected and utilized to prepare a novel polyesteramide (PEA) NF membrane that can reject SO42− but release Ca2+. Then it was employed in the pretreatment of seawater reverse osmosis to spatially isolate SO42− and Ca2+, thus removing the “foundation” for forming gypsum. Compared to the referenced NF270, the optimized sample denoted as DGA-PEA-NF has a looser structure with stronger negative charge, as well as a higher resistance to both organic fouling and chlorine attack. During the pretreatment of seawater, both the water permeability and SO42−/Ca2+ selectivity of the DGA-PEA-NF membrane were much higher than those of NF270; the seawater permeance and SO42−/Ca2+ selectivity of DGA-PEA-NF were 10.25 L m−2·h−1·bar−1 and 7.62, respectively, while those of NF270 were only 5.11 L m−2·h−1·bar−1 and 2.08. Consequently, the DGA-PEA-NF membrane effectively reduced the gypsum scaling both in NF and RO stages rather than just transferring the fouling problem forwards to NF stage. The implementation of this research is expected to provide guidance for a targeted fabrication of NF membranes, as well as support for the sustainable development of seawater desalination.

Multi-objective optimal day-ahead scheduling of desalination-hydrogen system powered by hybrid renewable energy sources

An energy system with desalination and hydrogen production and storage is a promising option for remote areas with shorelines, e.g., Middle East, to jointly manage electricity, desalinated water and hydrogen resources. Thus, a hybrid renewable energy system considering seawater reverse osmosis desalination, proton exchange membrane electrolyzer stacks, and also proton exchange membrane fuel cell, is proposed. This work focuses on the optimal operation problem of the system. It is established in a multi-objective optimization manner, with consideration of minimizing system total cost, power transmission and renewable energy curtailment. The problem is solved with Non-dominated Sorting Genetic Algorithm-III, a meta-heuristic method dedicated to multi-objective optimization. Results show through the solving of the optimization problem the optimal energy management strategy can be obtained, and in the studied scenario, the system can avoid 38–42% of carbon dioxide emission compared to conventional electricity generation and gray hydrogen production measures. The operational benefit of fuel cell is also verified. Compared to existing works, this work maintains the flexibility and cleanness of green hydrogen production components, consider more aspect in operation and can be solved with limited computational resources and obtain a satisfying result.

A Molecular Dynamics Study Employing Bimetallic Co–CuHAB Nanosheets for Seawater Desalination

Bimetallic MOFs, which contain two different types of metal nodes within their porous structures, have emerged as a novel class of materials that exhibit tunable properties, rendering them suitable for various applications. In this research, molecular dynamics (MD) simulations are conducted to assess the performance of 2D Hexaaminobenzene (HAB)-derived MOF membranes in reverse osmosis seawater desalination. The membranes display different Co:Cu metal node ratios and degrees of offset nanosheets, and their ion rejection rates and water flux values are compared. In particular, their behaviors are explained through the corresponding radial distribution functions, density distributions, and interaction energy values. Our findings reveal that of the four MOF membranes studied, CuHAB exhibits the best performance in terms of water flux. In addition, the pore diameter of the MOFs is dependent on the ratio of the Co and Cu nodes inside their respective MOF membranes. To achieve high water flux, it is recommended for the membranes to have large hydrophobic pores, while the membrane must display poor salt adsorption to prevent salt ions from permeating through. It is also observed that Co nodes exhibit greater affinity toward the O atoms of the water molecules and the Cl– ions than the Cu nodes. Due to the hydrophobic nature of the small CoHAB pores, offsetting the nanosheets that constitute the membranes can improve salt rejection but show no significant effect on water flux. Overall, this study shows that MD simulations can effectively determine the optimal ratio of metal nodes in bimetallic 2D MOF membranes to achieve desirable water flux values and ensure excellent salt rejection.

Evaluation of the nanofiltration of brines from seawater desalination plants as pre-treatment in a multimineral brine extraction process

Many materials essential to the European Union's (EU) economy lack primary resources, and the major suppliers of these materials are non-EU nations. It has been determined that seawater reverse osmosis (SWRO) desalination brines are a circular answer for the supply of critical elements. SWRO desalination brines, however, are distinguished by high concentrations of elements with negligible economic worth. (e.g., Na, Cl) compared to critical elements present in very low concentrations (e.g. Mg, B, Sc, V, In, Ga, Li, Mo, Rb). Therefore, an efficient separation pre-treatment is necessary to maximize the recovery efficiency in a brine extraction process. Nanofiltration (NF) was proposed as pre-treatment stage to separate monovalent from divalent ions and it was investigated if a Ca(II) removal stage was necessary before the NF to avoid scaling. The performances of three polyamide commercial membranes (NF270, Fortilife XC-N and PRO-XS2) treating SWRO brine (brine 1) and Ca(II)-free SWRO brine (after Ca(II) removal with sodium bicarbonate - brine 2) were evaluated in a closed circuit configuration as a function of the applied pressure from 6 to 30 bar.Results showed that NF was an efficient process to separate target elements present in seawater desalination brine into two different streams. Moreover, removal of Ca(II) before the NF step (brine 2) increased the selectivity between multivalent and monovalent species (higher rejection of multivalent and lower rejection of monovalent species compared to brine 1) for all the membranes tested, reaching the highest selectivity at 20 bar. At 20 bar, the polyamide membrane PRO-XS2 presented rejections of 71% for Ca(II) and 89% for Mg(II) and the highest selectivity in experiments with brine 2, being recommended for this application. In addition, the transport of species was characterized by membrane permeances by using the Solution-Electro-Diffusion-Film model. The scaling assessment at the membrane surface showed a lower scaling potential if Ca(II) was removed before the NF stage.

Selective lithium separation from desalination concentrates via the synergy of extractant mixtures

Seawater reverse osmosis (SWRO) desalination plants generate high volumes of concentrates, which contain, in addition to major salts, some elements of growing interest in minor concentrations. This is the case of lithium, highly demanded in the battery industry. In this work, the separation of Li+ from model SWRO brines has been evaluated by obtaining Li+ extraction curves with the combination of extractants DBM•TOPO and FDOD•TOPO, proving that both mixtures are capable of extracting Li+ under basic pH conditions, due to the keto-enolic tautomerism of the β-diketones. Li+ extraction values of 95.4 % for DBM•TOPO (pH = 12.2) and 100 % for FDOD•TOPO (pH = 9.0) were achieved. This behaviour was verified by the FT-IR analysis of the sample before and after the Li+ extraction. Finally, the selective separation of Li+ against other cations, such as Na+, K+, Mg2+, Ca2+ and Sr2+, present in the model brines at higher concentrations, was determined. Under mentioned experimental conditions, these cations are not extracted, reaching to Li+ selective separation close to 100 %. This study shows the first results on the selective extraction of lithium in complex SWRO brines, fostered through promising extractants mixtures showing a synergic effect towards Li+ in such multicomponent matrices.

Energy Efficiency Optimization in Onboard SWRO Desalination Plants Based on a Genetic Neuro-Fuzzy System

This work presents a novel intelligent control system based on a Genetic Neuro-Fuzzy tool to optimize and improve the performance of a seawater reverse osmosis desalination plant (SWRO) on board a marine vessel. This investigation pays special attention to minimizing energy consumption to improve the energy efficiency of this marine installation. The system analyzes measurements of different variables—seawater pH, seawater conductivity, permeate flow rate, permeate conductivity, and total energy consumed—in order to provide the most appropriate value of permeate flow rate control and operating pressure of the high-pressure pump (HPP). This intelligent method allows the plant to achieve output values nearer to the desired setpoints set by the plant operators.

Numerical study on the energy consumption characteristics of a novel integrated pump-motor unit for SWRO desalination system

Energy recovery device (ERD) is a critical component in seawater reverse osmosis (SWRO) desalination systems, which recovers hydraulic energy from the high-pressure brine and effectively reduces system energy consumption. In this thesis, a novel integrated seawater desalination pump-motor energy recovery device (ISPM-ERD) without the slipper/swashplate interface is proposed to further reduce energy consumption and improve system integration, which is able of concomitantly achieving seawater pressurization and energy recovery. A co-simulation multibody dynamic model with rigid-flexible coupling is applied to precisely examine the internal power loss of ISPM-ERD, especially volumetric loss and mechanical loss of the key lubricating interface. Besides, the influence of shaft rotational speed and working pressure on the power loss and overall efficiency of ISPM-ERD are comparatively investigated. In addition, a performance study of the presented ISPM-ERD is carried out based on the co-simulation model, which reveals the energy recovery efficiency and specific energy consumption (SEC) of ISPM-ERD under various operating conditions. The results indicate that the proposed ISPM-ERD is sufficient to meet the needs of the small-scale SWRO systems, whose energy recovery efficiency is more than 90.1 % in the 3.0–7.0 MPa operating pressure range and the SEC of freshwater production is 2.94 kW·h/m3 under rated working conditions.

Feasibility assessment of alternative environmentally friendly disinfection technique for reverse osmosis-based desalination process

In the seawater reverse osmosis (SWRO) process, the chlorine-based disinfection method poses significant incidental problems, such as producing disinfection by-products and damaging the SWRO membrane surface directly. Chlorine dioxide can control the biofouling layer and relatively stable disinfection approach during the operation. Major two perspective views, such as process stability (water flux and salt rejection) and membrane surface functionality, we evaluated chlorine dioxide feasibility as an alternative disinfection. Standard SWRO performance was evaluated at various operation conditions (inlet pressure and flow rate) using a customized SWRO system. For the stability of the chlorine dioxide disinfection approach, the chemical exposure test was conducted within the concentration and time-variant. While full total 30 days of long-term operation with continuous chlorine dioxide (0.5 mg/L) stripping during the SWRO desalination process, water flux and salt rejection rate maintain 26.7 L.min−1 and 99.7 % respectively.

A novel IEF-DLNN and multi-objective based optimizing control strategy for seawater reverse osmosis desalination plant

Over the past years, Seawater Desalination (SWD) has been enhanced regularly. In this desalination process, numerous technologies are available. The Reverse Osmosis (RO) process, which requires effectual control strategies, is the most commercially-dominant technology. Therefore, for SWD, a novel Interpolation and Exponential Function-centered Deep Learning Neural Network (IEF-DLNN) and multi-objective-based optimizing control system has been proposed in this research methodology. Initially, the input data are gathered; then, to control the desalination process, an optimal control technique has been utilized by employing Probability-centric Dove Swarm Optimization-Proportional Integral Derivative (PDSO-PID). The attributes of permeate are extracted before entering the RO process; after that, by utilizing the IEF-DLNN, the trajectory is predicted. For optimal selection, the extracted attributes are deemed if the trajectory is present, or else to mitigate energy consumption along with cost, the RO Desalination (ROD) is performed. In an experimental evaluation, regarding certain performance metrics, the proposed model's performance is analogized with the prevailing methodologies. The outcomes demonstrated that the proposed system achieved better performance.