TY - GEN
T1 - Technical and Economic Analyis of Rooftop Photovoltaic System
T2 - 4th International Conference on Smart Grid and Renewable Energy, SGRE 2024
AU - Bachour, Dunia
AU - Perez-Astudillo, Daniel
AU - Alhajri, Hissa
AU - Sanfilippo, Antonio
N1 - Publisher Copyright:
© 2024 IEEE.
PY - 2024
Y1 - 2024
N2 - Solar energy is one of the most widely available and abundant sources for energy generation. Several studies have shown that rooftop photovoltaic (PV) systems can efficiently generate electricity and support a country in its energy transition. In this work, the efficiency of solar energy generation in a residential housing complex, including 134 buildings, has been investigated. The solar PV rooftop potential was evaluated using an online map-based visualization application developed with in-situ solar radiation data acquired by the Qatar Environment and Energy Research Institute (QEERI), and GIS data provided by the Centre for GIS at the Ministry of Municipality (CGIS) in Qatar, including LiDAR elevation data, vector and raster representations of spatial data, and aerial photography for the area under study. The application runs as a GIS-based software platform and provides the estimation of rooftop PV systems yield alongside their financials, technical specifications, and carbon offsets in Qatar. The PV data output has been generated to compare the feasibility and techno economic analysis of rooftop PV systems showing a summary of installation scenarios in two different business models.
AB - Solar energy is one of the most widely available and abundant sources for energy generation. Several studies have shown that rooftop photovoltaic (PV) systems can efficiently generate electricity and support a country in its energy transition. In this work, the efficiency of solar energy generation in a residential housing complex, including 134 buildings, has been investigated. The solar PV rooftop potential was evaluated using an online map-based visualization application developed with in-situ solar radiation data acquired by the Qatar Environment and Energy Research Institute (QEERI), and GIS data provided by the Centre for GIS at the Ministry of Municipality (CGIS) in Qatar, including LiDAR elevation data, vector and raster representations of spatial data, and aerial photography for the area under study. The application runs as a GIS-based software platform and provides the estimation of rooftop PV systems yield alongside their financials, technical specifications, and carbon offsets in Qatar. The PV data output has been generated to compare the feasibility and techno economic analysis of rooftop PV systems showing a summary of installation scenarios in two different business models.
KW - PV residential
KW - PV rooftop
KW - solar radiation
KW - techno-economic
UR - http://www.scopus.com/inward/record.url?scp=85186639488&partnerID=8YFLogxK
U2 - 10.1109/SGRE59715.2024.10428891
DO - 10.1109/SGRE59715.2024.10428891
M3 - Conference contribution
AN - SCOPUS:85186639488
T3 - 4th International Conference on Smart Grid and Renewable Energy, SGRE 2024 - Proceedings
BT - 4th International Conference on Smart Grid and Renewable Energy, SGRE 2024 - Proceedings
PB - Institute of Electrical and Electronics Engineers Inc.
Y2 - 8 January 2024 through 10 January 2024
ER -