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