Effect of Thermodynamic Restriction on Energy Cost Optimization of RO Membrane Water Desalination

2009 ◽  
Vol 48 (13) ◽  
pp. 6010-6021 ◽  
Author(s):  
Aihua Zhu ◽  
Panagiotis D. Christofides ◽  
Yoram Cohen
2009 ◽  
Vol 3 (1) ◽  
pp. 8-16 ◽  
Author(s):  
Jian-Jun Qin ◽  
Boris Liberman ◽  
Kiran A. Kekre ◽  
Ado Gossan

Reverse osmosis (RO) has been widely applied in various water and wastewater treatment processes as a promising membrane technology. However, RO membrane fouling is a global issue, which limits it operating flux, decreases water production, increases power consumption and requires periodical membranes Cleaning-in-Place (CIP) procedure. This may result in low effectiveness, high cost and adds environmental issues related to the CIP solutions disposal. Forward osmosis (FO) or direct osmosis (DO) is the transport of water across a semi-permeable membrane from higher water chemical potential side to lower water chemical potential side, which phenomenon was observed in 1748. The engineered applications of FO/DO in membrane separation processes have been developed in food processing, wastewater treatment and seawater/brackish water desalination. In recent years, DO has been increasingly attractive for RO fouling control as it is highly efficient and environmentally friendly technique which is a new backwash technique via interval DO by intermittent injection of the high salinity solution without stoppage of high pressure pump or interruption of the operational process and allows keeping RO membrane continuously clean even in heavy bio-fouling conditions and operating RO membranes at high flux. This paper provides the state-of-the-art of the physical principles and applications of DO for RO fouling control as well as its strengths and limitations.


2021 ◽  
Vol 9 ◽  
Author(s):  
Yan Liao ◽  
Yong Liu ◽  
Chaoyu Chen ◽  
Lili Zhang

In this research, we propose a multi-objective optimization framework to minimize the energy cost while maintain the indoor air quality. The proposed framework is consisted with two stages: predictive modeling stage and multi-objective optimization stage. In the first stage, artificial neural networks are applied to predict the energy utility in real-time. In the second stage, an optimization algorithm namely firefly algorithm is utilized to reduce the energy cost while maintaining the required IAQ conditions. Industrial data collected from a commercial building in central business district in Chengdu, China is utilized in this study. The results produced by the optimization framework show that this strategy reduces energy cost by optimizing operations within the HAVC system.


Desalination ◽  
2008 ◽  
Vol 220 (1-3) ◽  
pp. 258-266 ◽  
Author(s):  
Mohamed Karime ◽  
S. Bouguecha ◽  
B. Hamrouni

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