Optimising the Operation of Renewable Energy-Driven Reverse Osmosis Desalination


The integration of Renewable Energy (RE) and Reverse Osmosis (RO) is essential for sustainable water production. However, it requires large-scale RO plants to accommodate fluctuating power inputs. Variable operation of RO plants by matching their load to available power, without battery back-up, has only been implemented for small-scale systems. This thesis presents a variable operation control procedure suitable for operating large-scale RO systems using RE. The procedure consists of two techniques, i.e., variable-speed operation and modular operation, for matching the RO load to varying degrees of RE fluctuation. The solutions presented were developed using a pilot RO plant that delivers similar performance to large-scale systems to allow implementation to such scale. Wind energy was used as a representation of an intermittent and fluctuating RE source. For variable-speed operation, multiple strategies were explored for varying the operating parameters according to available power. An advanced control system based on Model Predictive Control was designed and compared to a conventional Proportional-Integral-Differential controller. For modular operation, neural networks were developed to provide long- and short-term wind speed prediction for scheduling the RO units operation. The results showed that operation at variable recovery with constant brine flowrate delivered the lowest specific energy consumption and widest operation range for a system with an isobaric pressure exchanger. For a 10% step-change in permeate flowrate, the MPC controller improved the settling time by 47%. The long-term wind speed prediction was used to estimate the number of operational RO units for a day ahead for three random days, reaching a correlation of R2 0.78, 0.64, and 0.79 with the actual wind speed. This allowed scheduling the RO units to operate with a smooth operation profile that avoids unexpected shutdowns. By combining the optimised variable-speed and modular operations techniques, 90.9%, 91.5% and 91.4% of the available wind energy was utilised for Days 1, 2 and 3, which led to a high cumulative daily permeate production of 78 m3, 91.5 m3 and 123.4 m3, respectively. The solutions developed in this thesis showed that RO systems can be powered efficiently by RE using variable operation. This is fundamental for implementing this technology on a large-scale and decarbonising water production.

Divisions: College of Engineering & Physical Sciences > School of Infrastructure and Sustainable Engineering > Engineering Systems and Supply Chain Management
Additional Information: (c) Mohamed Tarek Mohamed Abelmonem Saleh Mito, 2021. Mohamed Tarek Mohamed Abelmonem Saleh Mito asserts his moral right to be identified as the author of this thesis. This copy of the thesis has been supplied on condition that anyone who consults it is understood to recognise that its copyright rests with its author and that no quotation from the thesis and no information derived from it may be published without appropriate permission or acknowledgement. If you have discovered material in Aston Publications Explorer which is unlawful e.g. breaches copyright, (either yours or that of a third party) or any other law, including but not limited to those relating to patent, trademark, confidentiality, data protection, obscenity, defamation, libel, then please read our Takedown Policy and contact the service immediately.
Institution: Aston University
Uncontrolled Keywords: Desalination,reverse osmosis,renewable energy,variable operation,model predictive control,wind speed prediction
Last Modified: 08 Dec 2023 08:58
Date Deposited: 07 Mar 2022 12:08
Completed Date: 2021-09
Authors: Mito, Mohamed Tarek (ORCID Profile 0000-0001-5851-8513)

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