Retrofitting assessment of a full-scale brackish water reverse osmosis desalination plant with a feed capacity of 600 m3/d

2019 ◽  
Vol 144 ◽  
pp. 72-78
Author(s):  
A. Ruiz-García ◽  
E. Dimitriou ◽  
I. Nuez
Keyword(s):  
Reverse Osmosis ◽  
Brackish Water ◽  
Full Scale ◽  
Desalination Plant ◽  
Reverse Osmosis Desalination

scholarly journals Full-Scale Seawater Reverse Osmosis Desalination Plant Simulator

2020 ◽  
Vol 53 (2) ◽  
pp. 16561-16568
Author(s):  
Mariam Elnour ◽  
Nader Meskin ◽  
Khlaed M. Khan ◽  
Raj Jain ◽  
Syed Zaidi ◽  
...  
Keyword(s):  
Reverse Osmosis ◽  
Full Scale ◽  
Desalination Plant ◽  
Seawater Reverse Osmosis ◽  
Reverse Osmosis Desalination

scholarly journals Analysis of long-term performance of full-scale reverse osmosis desalination plant using artificial neural network and tree model

2019 ◽  
Vol 25 (5) ◽  
pp. 763-770 ◽  
Author(s):  
Yongjun Choi ◽  
Younggeun Lee ◽  
Kwanghee Shin ◽  
Youngkyu Park ◽  
Sangho Lee
Keyword(s):  
Neural Network ◽  
Artificial Neural Network ◽  
Reverse Osmosis ◽  
Full Scale ◽  
Tree Model ◽  
Desalination Plant ◽  
Long Term Performance ◽  
Term Performance ◽  
Reverse Osmosis Desalination

The reverse osmosis (RO) technology is currently the leading desalination method. However, until recently, application of RO technology on a large scale has been primarily limited by membrane fouling. The mechanism of fouling is complex, which is not well understood in full-scale plants. Although many studies about modeling and prediction of fouling have been done, in most cases, the experimental data set of lab or pilot scale systems, which may not show fouling characteristics well in full-scale systems were used. In this study, both artificial neural network (ANN) model and tree model (TM) was evaluated to analyze long-term performance of full scale reverse osmosis desalination plant. The results of application of the ANN and TM indicated high correlation coefficients between the measured and simulated output variables. However, it is not easy to use ANN for the full scale plant operation because the final model is not expressed as a form of mathematical functions. TM has advantages over ANN because the model can be obtained as forms of simple function and it showed reasonably high <i>R</i><sup>2</sup>. Therefore, TM is shown to be more adequate than ANN for developing models in which the full-scale RO plant data is considered as an input.

scholarly journals Stand-Alone Direct Current Power Network Based on Photovoltaics and Lithium-Ion Batteries for Reverse Osmosis Desalination Plant

Energies ◽  
2021 ◽  
Vol 14 (10) ◽  
pp. 2772
Author(s):  
Vishwas Powar ◽  
Rajendra Singh
Keyword(s):  
Reverse Osmosis ◽  
Direct Current ◽  
Cyber Security ◽  
Large Scale ◽  
Lithium Ion ◽  
Economic Feasibility ◽  
Power Network ◽  
Variable Effect ◽  
Desalination Plant ◽  
Reverse Osmosis Desalination

Plummeting reserves and increasing demand of freshwater resources have culminated into a global water crisis. Desalination is a potential solution to mitigate the freshwater shortage. However, the process of desalination is expensive and energy-intensive. Due to the water-energy-climate nexus, there is an urgent need to provide sustainable low-cost electrical power for desalination that has the lowest impact on climate and related ecosystem challenges. For a large-scale reverse osmosis desalination plant, we have proposed the design and analysis of a photovoltaics and battery-based stand-alone direct current power network. The design methodology focusses on appropriate sizing, optimum tilt and temperature compensation techniques based on 10 years of irradiation data for the Carlsbad Desalination Plant in California, USA. A decision-tree approach is employed for ensuring hourly load-generation balance. The power flow analysis evaluates self-sufficient generation even during cloud cover contingencies. The primary goal of the proposed system is to maximize the utilization of generated photovoltaic power and battery energy storage with minimal conversions and transmission losses. The direct current based topology includes high-voltage transmission, on-the-spot local inversion, situational awareness and cyber security features. Lastly, economic feasibility of the proposed system is carried out for a plant lifetime of 30 years. The variable effect of utility-scale battery storage costs for 16–18 h of operation is studied. Our results show that the proposed design will provide low electricity costs ranging from 3.79 to 6.43 ¢/kWh depending on the debt rate. Without employing the concept of baseload electric power, photovoltaics and battery-based direct current power networks for large-scale desalination plants can achieve tremendous energy savings and cost reduction with negligible carbon footprint, thereby providing affordable water for all.

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