Published October 2019 | Version v1
Journal article

Modelling and optimization of modular system for power generation from a salinity gradient

  • 1. School of Civil and Environmental Engineering, University of Technology Sydney, 15 Broadway, Ultimo, NSW 2007 (Australia)
  • 2. Dipartimento di Ingegneria, Università degli Studi di Palermo, viale delle Scienze Ed.6, 90128, Palermo (Italy)

Description

Pressure retarded osmosis has been proposed for power generation from a salinity gradient resource. The process has been promoted as a promising technology for power generation from renewable resources, but most of the experimental work has been done on a laboratory size units. To date, pressure retarded osmosis optimization and operation is based on parametric studies performed on laboratory scale units, which leaves a gap in our understanding of the process behaviour in a full-scale modular system. A computer model has been developed to predict the process performance. Process modelling was performed on a full-scale membrane module and impact of key operating parameters such as hydraulic feed pressure and feed and draw solution rates were evaluated. Results showed that the optimum fraction of feed/draw solution in a mixture is less than what has been earlier proposed ratio of 50% and it is entirely dependent on the salinity gradient resource concentration. Furthermore, the optimized pressure retarded osmosis process requires a hydraulic pressure less than that in the normal (unoptimized) process. The results here demonstrate that the energy output from the optimized pressure regarded osmosis process is up to 54% higher than that in the normal (unoptimized) process.

Additional details

Identifiers

DOI
10.1016/j.renene.2019.03.138;
PII
S0960148119304598;

Publishing Information

Journal Title
Renewable Energy
Journal Volume
141
Journal Page Range
p. 139-147
ISSN
0960-1481
CODEN
RNENE3

INIS

Country of Publication
United Kingdom
Country of Input or Organization
International Atomic Energy Agency (IAEA)
INIS RN
55022654
Subject category
S09: BIOMASS FUELS; S37: INORGANIC, ORGANIC, PHYSICAL AND ANALYTICAL CHEMISTRY;
Descriptors DEI
BIOMASS; COMPUTERIZED SIMULATION; HYDRAULICS; MEMBRANES; OPTIMIZATION; ORGANIC COMPOUNDS; OSMOSIS; PARAMETRIC ANALYSIS; POWER GENERATION; SALINITY GRADIENTS
Descriptors DEC
DIFFUSION; ENERGY SOURCES; FLUID MECHANICS; MECHANICS; RENEWABLE ENERGY SOURCES; SIMULATION

Optional Information

Copyright
Copyright (c) 2019 Elsevier Ltd. All rights reserved.