Renewable Energy Planning
Solid Waste Management
Estimating solar energy production in urban areas for electric vehicles
Master thesis,   ,
In this research, the study area is the new Cairo city which has a high potential for harvesting solar energy, buildings in each compound have the same height, which does not cast shade on other buildings affecting PV efficiency. When applying GIS and RS techniques in New Cairo city, it is found that environmental factors - such as bare soil - affect the accuracy of the result, which reached 67% on the city scale. Researching more minor scales, such as compounds, required Very High Resolution (VHR) satellite images with a spatial resolution of up to 0.5 meter. The RS techniques applied in this research included supervised classification, and feature extraction, on Pleiades-1b VHR. On the compound scale, the accuracy assessment for the samples ranged between 74.6% and 96.875%.
Estimating the PV energy production requires solar data; which was collected using a weather station and a pyrometer at the American University in Cairo, which is typical of the neighboring compounds in the new Cairo region. It took three years to collect the solar incidence data. The Hay- Devis, Klucher, and Reindl (HDKR) model is then employed to extrapolate the solar radiation measured on horizontal surfaces β =0°, to that on tilted surfaces with inclination angles β =10°, 20°, 30° and 45°. The calculated (with help of GIS and Solar radiation models) net rooftop area available for capturing solar radiation was determined for sample New Cairo compounds . The available rooftop areas were subject to the restriction that all the PVs would be coplanar, none of the PVs would protrude outside the rooftop boundaries, and no shading of PVs would occur at any time of the year; moreover typical other rooftop occupied areas, and actual dimensions of typical roof top PVs were taken into consideration. From those calculations, both the realistic total annual Electrical energy produced by the PVs and their daily monthly energy produced are deduced. The former is relevant if the PVs are tied to a grid, whereas the other is more relevant if it is not; optimization is different for both. Results were extended to estimate the total number of cars that may be driven off PV converted solar radiation per home, for different scenarios.
Estimating Rooftops’ Suitability for PVs Using Pleiades-1B Satellite Image for Charging Electric Vehicles in New Cairo, Egypt.
Shaimaa Ahmed, Mohamed Amr Serag-Eldin, and Mohamed El-Morsi
International Solar Energy Society, EuroSun2022 Proceedings,   ,
radiation data on a horizontal surface were obtained from a weather station in New Cairo City (Egypt). Second, the
Hay & Davies, Klucher, and Reindl (HDKR) model was used to calculate the available solar radiation on tilted
surfaces. Finally, rooftops were identified and extracted from a Very High-Resolution (VHR) satellite image using
Remote Sensing and Geographic Information Sciences techniques. The flat rooftops’ extraction accuracy ranged
between 74.6% and 96.875%. The area required for generating enough energy for one Electric Vehicle (EV) was
estimated for both summer and winter. Avoiding shades from parapet walls and following the country’s building
codes, the water tanks and rooftop rooms were considered for PV installation. The results showed that PV rooftops
could provide electricity for charging EVs in neighborhoods with different urban designs. The variables affecting the
solar energy potential for EV charging are suitable rooftop areas and available solar radiation.
A method and apparatus for generating energy (Application)
WIPO (PCT),   ,