• AWWA MTC64614
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AWWA MTC64614

  • RO Process Design Optimization Based on Stochastic Cost Estimation Model Coupled with Process Performance Simulation Model
  • Conference Proceeding by American Water Works Association, 03/01/2007
  • Publisher: AWWA

$12.00$24.00


A survey was performed over four seawater reverse osmosis (RO) desalination plants tostudy the current status of boron rejection in the seawater desalination process. The survey found thatboron rejection ranged from 65 to 85 %, with some plants producing water having boronconcentration over 0.5 mg/L, a maximum contaminant level in drinking water suggested in the World Health Organization (WHO) Guidelines. While installation of boron reduction systems increase the costs of the process,several system design options are available to meet the same target water quality criteriawith highly varying costs. The objective of this study was to develop an algorithm based on adeterministic process model and a stochastic cost model that can be used to select the systemwith the lowest overall costs and risk. A deterministic predictive model was first developed tosimulate the performance of a spiral wound module in terms of boron rejection, salt (TDS)rejection and overall product recovery. The model was verified using a set of pilot-scaleexperiments performed under different conditions using synthetic seawaters that contained boron.This model was then modified to simulate the full-scale RO process performance under varyingdesign and operating conditions to meet required water quality criteria in terms of boronrejection. It was further combined with a stochastic cost-estimation model that estimates netpresent value (NPV) of future costs, which was used as an overall performance measure. Theinput probability models for the stochastic cost model were developed by fitting the distributionfunctions to random data. The key factors with uncertainties that have a significant impact oncost analysis include membrane costs, electricity prices, inflation rates, interest rates anddiscount rates. Four design options were selected from ten available design options based on theexpected cost (NPV) and risk (variance in cost) for process optimization based on the coupledmodel. Includes 11 references, tables, figures.

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