期刊
DESALINATION AND WATER TREATMENT
卷 225, 期 -, 页码 364-370出版社
DESALINATION PUBL
DOI: 10.5004/dwt.2021.27212
关键词
Desalination; Reverse osmosis; Artificial neural networks; Small vessels
资金
- FEDER funds
- INTERREGMAC 2014-2020 Programme of the European Union, part of the DESAL+ Project [MAC/1.1a/094]
- E5DES project [MAC2/1.1a/309]
This study analyzed the energy consumption of a small-scale seawater reverse osmosis desalination plant and applied an artificial neural network model to optimize its performance. By considering different parameters such as flow rate, pressure, and water conductivity, the optimal pressure points in the system were estimated to meet both water quality and low energy consumption requirements.
Desalination in the marine world has always been one of the most widely used resources for obtaining fresh water. Its greatest disadvantage is energy consumption, which has led to many studies to investigate how to reduce it. This work presents the results obtained from analysing the energy consumption of a small-scale seawater reverse osmosis desalination plant and its application in small marine vessels. An artificial neural network model was applied to optimise the performance of the plant. For this research, different parameters have been considered, namely, the flow rate, pressure and conductivity of the water demanded in the vessel. In the experimental study, the optimal pressure points applied in the system are estimated to satisfy both the water quality and low energy consumption requirements.
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