A New Methodology for Estimating the Potential for Photovoltaic Electricity Generation on Urban Building Rooftops for Self-Consumption Applications

As the world increasingly embraces renewable energy as a sustainable power source, accurately assessing of solar energy potential becomes paramount. Photovoltaic (PV) systems, especially those integrated into urban rooftops, offer a promising solution to address the challenges posed by aging energy grids and rising fossil fuel prices. However, optimizing the placement of PV panels on rooftops remains a complex task due to factors like building shape, location, and the surrounding environment. This study introduces the Roof-Solar-Max methodology, which aims to maximize the placement of PV panels on urban rooftops while avoiding shading and panel overlap. Leveraging geographic information systems technology and 3D models, this methodology provides precise estimates of PV generation potential. Key contributions of this research include a roof categorization model, identification of PV-ready rooftops, optimal spatial distribution of PV panels, and innovative evaluation technology. Practical implementation in a real urban setting demonstrates the methodology’s utility for decision making in the planning and development of solar energy systems in urban areas. The main findings highlight substantial potential for PV energy generation in the studied urban area, with capacities reaching up to 444.44 kW. Furthermore, implementing PV systems on residential rooftops has proven to be an effective strategy for reducing CO2 emissions and addressing climate change, contributing to a cleaner and more sustainable energy mix in urban environments.

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Publication Details

Journal
Smart Cities
Published
2024-12-04
DOI
https://doi.org/10.3390/smartcities7060146
Citations
9
Primary Topic
Solar Radiation and Photovoltaics
Type
article
Field-Weighted Citation Impact
3.13
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article

A New Methodology for Estimating the Potential for Photovoltaic Electricity Generation on Urban Building Rooftops for Self-Consumption Applications

Danny Ochoa-Correa, Edisson Villa‐Ávila, Francisco Jurado, Paúl Arévalo et al.
9 citations
Smart Cities
Solar Radiation and Photovoltaics
3.13
article

A New Methodology for Estimating the Potential for Photovoltaic Electricity Generation on Urban Building Rooftops for Self-Consumption Applications

Danny Ochoa-Correa, Edisson Villa‐Ávila, Francisco Jurado, Paúl Arévalo, Michael Villa-Ávila, Emilia Sempértegui-Moscoso
article en
9 citations

Abstract

As the world increasingly embraces renewable energy as a sustainable power source, accurately assessing of solar energy potential becomes paramount. Photovoltaic (PV) systems, especially those integrated into urban rooftops, offer a promising solution to address the challenges posed by aging energy grids and rising fossil fuel prices. However, optimizing the placement of PV panels on rooftops remains a complex task due to factors like building shape, location, and the surrounding environment. This study introduces the Roof-Solar-Max methodology, which aims to maximize the placement of PV panels on urban rooftops while avoiding shading and panel overlap. Leveraging geographic information systems technology and 3D models, this methodology provides precise estimates of PV generation potential. Key contributions of this research include a roof categorization model, identification of PV-ready rooftops, optimal spatial distribution of PV panels, and innovative evaluation technology. Practical implementation in a real urban setting demonstrates the methodology’s utility for decision making in the planning and development of solar energy systems in urban areas. The main findings highlight substantial potential for PV energy generation in the studied urban area, with capacities reaching up to 444.44 kW. Furthermore, implementing PV systems on residential rooftops has proven to be an effective strategy for reducing CO2 emissions and addressing climate change, contributing to a cleaner and more sustainable energy mix in urban environments.

Smart CitiesVol. 7(6)
University of Cuenca (EC), Universidad de Jaén (ES)
Openalex Percentile: Top 7%
Solar Radiation and Photovoltaics
3.13
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