Economic Assessment Based on Energy Consumption on the Capacities in Seawater Reverse Osmosis (SWRO) Plant in Korea

Ion-exchange membrane electrodialytic salt production using brine discharged from a reverse osmosis seawater desalination plant

Waste energy recovery in seawater reverse osmosis desalination plants. Part 1: Review

Preliminary experimental analysis of a small-scale prototype SWRO desalination plant, designed for continuous adjustment of its energy consumption to the widely varying power generated by a stand-alone wind turbine

Inorganic scaling is a major concern for thermal and reverse osmosis (RO) seawater desalination plants, which are the key technologies for meeting the increasing freshwater demand. Membrane scaling is a detrimental effect in both thermal and RO process that reduces its performance particularly by reducing the water flux and causing membrane wetting. In this chapter, the formation mechanisms of inorganic scaling in thermal and reverse osmosis plants are discussed. The factors contributing to scale formation such as temperature, pH, and ionic strength of the treated water and the scale indices frequently used to predict the scale formation are explained. Finally, prevention methodologies developed to mitigate inorganic scaling (pre-treatment strategies, cleaning processes, advanced materials, etc.) are enumerated and discussed. Overall, this chapter provides a fundamental perspective of the inorganic scaling in thermal and reverse osmosis seawater desalination plants.

Energy consumption assessment of 4,000 m3/d SWRO desalination plants

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

Seawater desalination by reverse osmosis : Plant design, performance data, operation and maintenance (Tanajib, Arabian Gulf Coast)

Exergo-economic analysis of a seawater reverse osmosis desalination plant with various retrofit options

In this present paper, a risk analysis approach is applied to an Algerian reverse osmosis seawater desalination plant using the MADS MOSAR method. MADS MOSAR method is a stepwise risk analysis approach containing many phases. Our work begins with analyzing a review of past accidents triggered by the Ben in Saf Water Company (BWC) seawater desalination plant locating in the Algerian coast in Ain Temouchent region and analyzing their similar seawater desalination plants (or plants that using similar and potential equipment). Then, the MADS MOSAR method will apply essentially for the macroscopic vision (Module A). The macroscopic vision corresponds to a main risk analysis. In the current case study, we were able to identify eight subsystems where sources and scenarios of hazards are identified, accident scenarios are assessed, recognized and ranked by Severity×Probability grid. We found twenty-six scenarios whose we were able to assess them in function of their and using probability x severity grid criteria. At the end of the analysis, we were able to define and suggest the most appropriate prevention and protection barriers for the potential elements in the studied seawater desalination plant, including pipelines, transformers, compressors, high pressure pumps, pressure vessels and energy recovery devices.

Fouling control in SWRO desalination during harmful algal blooms: A historical review and future developments

Influence of site-specific parameters on environmental impacts of desalination

Our aim was to analyze, monitor, and predict the outcomes of processes in a full-scale seawater reverse osmosis (SWRO) desalination plant using multivariate statistical techniques. Multivariate analysis of variance (MANOVA) was used to investigate the performance and efficiencies of two SWRO processes, namely, pore controllable fiber filter-reverse osmosis (PCF-SWRO) and sand filtration-ultra filtration-reverse osmosis (SF-UF-SWRO). Principal component analysis (PCA) was applied to monitor the two SWRO processes. PCA monitoring revealed that the SF-UF-SWRO process could be analyzed reliably with a low number of outliers and disturbances. Partial least squares (PLS) analysis was then conducted to predict which of the seven input parameters of feed flow rate, PCF/SF-UF filtrate flow rate, temperature of feed water, turbidity feed, pH, reverse osmosis (RO)flow rate, and pressure had a significant effect on the outcome variables of permeate flow rate and concentration. Root mean squared errors (RMSEs) of the PLS models for permeate flow rates were 31.5 and 28.6 for the PCF-SWRO process and SF-UF-SWRO process, respectively, while RMSEs of permeate concentrations were 350.44 and 289.4, respectively. These results indicate that the SF-UF-SWRO process can be modeled more accurately than the PCF-SWRO process, because the RMSE values of permeate flowrate and concentration obtained using a PLS regression model of the SF-UF-SWRO process were lower than those obtained for the PCF-SWRO process.

Seawater pretreatment by continuous sand filter for seawater RO (reverse osmosis) desalination plant

Behaviour of the asynchronous electric motors to reduction of energy consumption in reverse osmosis plants

Development of the most adequate pre-treatment for high capacity seawater desalination plants with open intake