Feasibility Study of SMART MONOFLOAT Hydrokinetic Power for the Rural Households in Naga Hammadi, Egypt

Author(s):  
Fahd Diab ◽  
Hai Lan

Hybrid Renewable Energy System (HRES) is an attractive system for stand-alone electrification in remote areas. The hydrokinetic power avoids all the disadvantages of hydropower, unlike dams that have obstructed the natural water flow and ended up displacing animals and people. The main objective of this research work is to provide a feasibility study of using SMART MONOFLOAT hydrokinetic power in hybrid photovoltaic (PV)/HKT/diesel/battery system to satisfy the electrical energy needs for the selected rural households in Naga Hammadi, Egypt in this study. The SMART MONOFLOAT hydrokinetic turbine has been used as it was developed to produce a maximum amount of electrical power with the kinetic energy of flowing water. The well-known Hybrid Optimization of Multiple Electric Renewables (HOMER) software is used as a software tool in this study. The 22-year average monthly solar radiation data for the selected rural households in Naga Hammadi, located at latitude of 26.013 and longitude of 32.32 was obtained from National Aeronautics and Space Administration (NASA) database. The average monthly current velocity data of the Nile River used in this study was collected for a single year during 1991 after construction of the Aswan Dam in 1904. According to the simulation results in this work, it was found that the optimum HRES consisting of; 90 kW PV panels, 90 kW HKTs, 22 kW diesel generators, 60 kW power converters and 225 batteries. In addition to that, a great reduction in greenhouse gases (GHG) emission during the project lifetime could be achieved by using the optimum system.

Energies ◽  
2021 ◽  
Vol 14 (21) ◽  
pp. 7084
Author(s):  
Fadi Kahwash ◽  
Basel Barakat ◽  
Ahmad Taha ◽  
Qammer H. Abbasi ◽  
Muhammad Ali Imran

This study focuses on improving the sustainability of electrical supply in the healthcare system in the UK, to contribute to current efforts made towards the 2050 net-zero carbon target. As a case study, we propose a grid-connected hybrid renewable energy system (HRES) for a hospital in the south-east of England. Electrical consumption data were gathered from five wards in the hospital for a period of one year. PV-battery-grid system architecture was selected to ensure practical execution through the installation of PV arrays on the roof of the facility. Selection of the optimal system was conducted through a novel methodology combining multi-objective optimisation and data forecasting. The optimisation was conducted using a genetic algorithm with two objectives (1) minimisation of the levelised cost of energy and (2) CO2 emissions. Advanced data forecasting was used to forecast grid emissions and other cost parameters at two year intervals (2023 and 2025). Several optimisation simulations were carried out using the actual and forecasted parameters to improve decision making. The results show that incorporating forecasted parameters into the optimisation allows to identify the subset of optimal solutions that will become sub-optimal in the future and, therefore, should be avoided. Finally, a framework for choosing the most suitable subset of optimal solutions was presented.


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