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Shaimaa Ahmed
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Shaimaa Ahmed

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Shaimaa
Ahmed
Shaimaa Ahmed
shahmed
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Yes
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Profile Overview

Researcher
Education
GIS, remote sensing
No
Female

Capabilities


The American University in Cairo
2018    -   
Master of Science in Environmental Engineering
Environmental Engineering
GIS
Renewable Energy Planning
Sustainability
Solid Waste Management

Clark University
2006    -    2008
Master of Arts in Geographic Information Sciences for Development and Environment
GIS
Remote Sensing
Statistics
ESRI internship

Estimating solar energy production in urban areas for electric vehicles
Shaimaa Ahmed
Master thesis,   ,  

Cities have a high potential for solar energy from PVs installed on buildings' rooftops. There is an increased demand for solar energy in cities to reduce the negative effect of climate change. The thesis investigates solar energy potential in urban areas. It tries to determine how to detect and identify available rooftop areas, how to calculate suitable ones after excluding the effects of the shade, and the estimated energy generated from PVs. Geographic Information Sciences (GIS) and Remote Sensing (RS) are used in solar city planning. The goal of this research is to assess available and suitable rooftops areas using different GIS and RS techniques for installing PVs and estimating solar energy production for a sample of six compounds in New Cairo, and explore how to map urban areas on the city scale.

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.
https://fount.aucegypt.edu/etds/1996/


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,   ,  

Studying the potential of solar energy PV rooftops requires assessing solar energy and rooftop areas. First, solar
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.
http://ises-proceedings.pse-co.de/paper/eurosun2022/eurosun2022-0096-Ahmed.pdf


A method and apparatus for generating energy (Application)
Shaimaa Ahmed
WIPO (PCT),   ,  

An energy generation system (1) comprising at least one underground chamber (2) surrounded at least partially by soil (3) which is warmed up by solar and/or geothermal energy to heat up a fluid (F) within said underground chamber (2), and a turbine (8) driven by the heated up fluid (F) to generate electrical energy.
https://patents.google.com/patent/WO2014114335A1/en

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07 Sep 2020
10 Nov 2023
09 Nov 2023

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