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Estimating Solar Energy Production in Urban Areas for Electric Vehicles
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 ide...
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2023
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| _version_ | 1867613431559880704 |
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| access_status_str | Open Access |
| author | Ahmed, Shaimaa |
| author_browse | Ahmed, Shaimaa |
| author_facet | Ahmed, Shaimaa |
| author_sort | Ahmed, Shaimaa |
| collection | Thesis |
| description | 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. |
| format | Thesis |
| id | oai:fount.aucegypt.edu:etds-3029 |
| institution | American University in Cairo (Egypt) |
| last_indexed | 2026-06-10T12:35:59.828Z |
| license_str | Not specified — see source repository |
| provenance_str_mv | Harvested via OAI-PMH from AUC Knowledge Fountain — bepress |
| publishDate | 2023 |
| publishDateRange | 2023 |
| publishDateSort | 2023 |
| publisher | AUC Knowledge Fountain |
| publisherStr | AUC Knowledge Fountain |
| record_format | dspace |
| source_str | AUC Knowledge Fountain — bepress |
| spelling | oai:fount.aucegypt.edu:etds-3029 Estimating Solar Energy Production in Urban Areas for Electric Vehicles Ahmed, Shaimaa 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. 2023-01-31T08:00:00Z thesis application/pdf https://fount.aucegypt.edu/etds/1996 https://fount.aucegypt.edu/context/etds/article/3029/viewcontent/Shaimaa_Ahmed_thesis.pdf Theses and Dissertations AUC Knowledge Fountain Geographic Information Sciences Remote Sensing Solar Energy Solar Planning PV energy production PV rooftops The Hay- Devis Klucher and Reindl (HDKR) model Electric Vehicles Desert Cities. Energy Systems Environmental Engineering Geographic Information Sciences Remote Sensing Spatial Science Urban, Community and Regional Planning |
| spellingShingle | Geographic Information Sciences Remote Sensing Solar Energy Solar Planning PV energy production PV rooftops The Hay- Devis Klucher and Reindl (HDKR) model Electric Vehicles Desert Cities. Energy Systems Environmental Engineering Geographic Information Sciences Remote Sensing Spatial Science Urban, Community and Regional Planning Ahmed, Shaimaa Estimating Solar Energy Production in Urban Areas for Electric Vehicles |
| title | Estimating Solar Energy Production in Urban Areas for Electric Vehicles |
| title_full | Estimating Solar Energy Production in Urban Areas for Electric Vehicles |
| title_fullStr | Estimating Solar Energy Production in Urban Areas for Electric Vehicles |
| title_full_unstemmed | Estimating Solar Energy Production in Urban Areas for Electric Vehicles |
| title_short | Estimating Solar Energy Production in Urban Areas for Electric Vehicles |
| title_sort | estimating solar energy production in urban areas for electric vehicles |
| topic | Geographic Information Sciences Remote Sensing Solar Energy Solar Planning PV energy production PV rooftops The Hay- Devis Klucher and Reindl (HDKR) model Electric Vehicles Desert Cities. Energy Systems Environmental Engineering Geographic Information Sciences Remote Sensing Spatial Science Urban, Community and Regional Planning |
| url | https://fount.aucegypt.edu/etds/1996 https://fount.aucegypt.edu/context/etds/article/3029/viewcontent/Shaimaa_Ahmed_thesis.pdf |
| work_keys_str_mv | AT ahmedshaimaa estimatingsolarenergyproductioninurbanareasforelectricvehicles |