الفهرس 
INTRODUCTIONOnly 14 pages are availabe for public view
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Abstract
Due to the challenges of climate change and the scarcity of energy and water, the coupling between different renewable energy sources (RES) and water desalination systems becomes urgently necessary. Desalination systems that rely on renewable energy sources have been widely discussed as an innovative approach to water desalination in an economical and environmentally friendly way.
Recently, photovoltaic (PV) systems have become available and widely used in desalination applications with low energy consumption. In addition, various RES such as wind systems either (VAWT or HAWT), concentrated solar power plants (CSP), and fuel cell (FC). can be coupled with desalination systems.
The potential of renewable energy sources in desalination systems can be used in a more economically efficient manner, as the energy produced is consumed to produce drinking water that can be stored for a long time before consumption.
Reverse osmosis (RO) has become the most popular technology for desalination, this is because the reverse osmosis desalination plants require less energy, less investment, and lower maintenance cost than other alternative desalination processes.
Firstly, this work, presents new modeling techniques for evaluating the performance of PV panels, vertical-axis wind turbines (VAWT), and horizontal-axis wind turbines (HAWT). Two methods are implemented to evaluate and simulate the designed models based on actual data points from various manufacturing manuals. The first technique is based on curve fitting while the artificial neural network (ANN) is the second method. The developed models can predict the operating performance characteristics of PV, VAWT and HAWT based only on the demand power. Hence, it can easily assist the designer to select a suitable unit before the installation process. The PV model can predict the short circuit current, open circuit voltage, voltage and current at maximum power, module efficiency and the module Energy range from 5W to 350W per module. Moreover, the wind turbine models can predict the cut-in wind speed, rated speed, rotor diameter, rotor speed, hub height and the turbine cost for a power range of 0.1kW to 100kW for VAWT and from 0.5kW to 8000kW for HAWT. The results show that the ANN method provides a higher match with the actual data compared to the curve fitting method. The models are conducted via Matalb/Simulink.
Moreover, new models of concentrated solar power plants (CSP), fuel cells and diesel generators are presented to be then coupled with different configurations of the RO plant. The models are implemented based on steady state performance using Matlab’s Graphical User Interface (GUI). In the case of the Reverse Osmosis (RO) unit, configurations with and without an energy recovery device have been considered. Furthermore, three different RO plant configurations (RO basic, RO-PWT, RO-PEX) have been modeled under variable operating conditions and the investigated, simulated results and the curves will show the different parameters to distinguish the best type that the designer will choose among them. Firstly, the calculation of the number of vessels corresponding to the productivity of the desalination plants while achieving the best output of the plant parameters required. Moreover, the effect of changing the number of pressure vessels, the effect of changing sea water salinity and the effect of changing sea water temperature on the specific energy consumption, pressure, pump power and fresh water salinity for different RO types studied,
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and the comparison charts introduced to distinguishes the best choice of the planets type.
Finally, techno-economic analysis is discussed for the following cases: PV-RO, HAWT-RO, VAWT-RO, and CSP-RO, Fuel cell-RO, and diesel generator-RO systems. The study can provide the total annual costs of the system and the water production cost for each case. The model is simulated using Matlab/Simulink and presented good results.