TY - CHAP
T1 - A new innovative methodology for photovoltaic integration on rooftops for cost reduction and reduced grid dependency
AU - Villa-Ávila, Edisson
AU - Cano, Antonio
AU - Arévalo, Paul
AU - Ochoa-Correa, Danny
AU - Jurado, Francisco
N1 - Publisher Copyright:
© 2025 selection and editorial matter, A. J. Singh, Nikita Gupta, Sanjay Kumar, Sumit Sharma, Subho Upadhyay, and Sandeep Kumar.
PY - 2025/1/1
Y1 - 2025/1/1
N2 - As the global demand for sustainable energy rises, accurately assessing the potential of solar energy becomes crucial. Photovoltaic systems, particularly those integrated into urban rooftops, offer a promising solution to address challenges associated with outdated energy grids and increasing fossil fuel costs. However, achieving the optimal placement of photovoltaic panels on rooftops remains challenging due to factors such as building morphology, location, and the surrounding environment. In this context, this chapter introduces the roof-solar methodology, designed to enhance the placement of photovoltaic panels in urban environments by avoiding shading and overlaps. Based on geographic information system technologies and three-dimensional models, this methodology provides precise estimates of photovoltaic energy generation potential. Key contributions of this work include a roof categorization model, the identification of suitable roofs for photovoltaic panel installation, as well as the optimal spatial distribution of these devices, and innovative assessment technologies. The practical application of this methodology in real urban environments confirms its utility for decision-making in the planning and development of solar energy systems. The results highlight a significant potential for photovoltaic energy generation in the studied urban area, with capacities reaching up to 343 kW. Furthermore, implementing photovoltaic systems on residential rooftops have proven to be an effective strategy in reducing CO2 emissions and addressing climate change, contributing to a cleaner and more sustainable energy matrix in urban settings.
AB - As the global demand for sustainable energy rises, accurately assessing the potential of solar energy becomes crucial. Photovoltaic systems, particularly those integrated into urban rooftops, offer a promising solution to address challenges associated with outdated energy grids and increasing fossil fuel costs. However, achieving the optimal placement of photovoltaic panels on rooftops remains challenging due to factors such as building morphology, location, and the surrounding environment. In this context, this chapter introduces the roof-solar methodology, designed to enhance the placement of photovoltaic panels in urban environments by avoiding shading and overlaps. Based on geographic information system technologies and three-dimensional models, this methodology provides precise estimates of photovoltaic energy generation potential. Key contributions of this work include a roof categorization model, the identification of suitable roofs for photovoltaic panel installation, as well as the optimal spatial distribution of these devices, and innovative assessment technologies. The practical application of this methodology in real urban environments confirms its utility for decision-making in the planning and development of solar energy systems. The results highlight a significant potential for photovoltaic energy generation in the studied urban area, with capacities reaching up to 343 kW. Furthermore, implementing photovoltaic systems on residential rooftops have proven to be an effective strategy in reducing CO2 emissions and addressing climate change, contributing to a cleaner and more sustainable energy matrix in urban settings.
UR - https://www.scopus.com/pages/publications/85214902618
U2 - 10.1201/9781003581246-6
DO - 10.1201/9781003581246-6
M3 - Capítulo
AN - SCOPUS:85214902618
SN - 9781040273586
T3 - Artificial Intelligence and Machine Learning Applications for Sustainable Development
SP - 150
EP - 176
BT - Artificial Intelligence and Machine Learning Applications for Sustainable Development
PB - CRC Press
ER -