Solar Potential Uncertainty in Building Rooftops as a Function of Digital Surface Model Accuracy
Solar cadasters are excellent tools for determining the most suitable rooftops and areas for PV deployment in urban environments. There are several open models that are available to compute the solar potential in cities. The Solar Energy on Building Envelopes (SEBE) is a powerful model incorporated...
| Main Authors: | , |
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| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2023-01-01
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| Series: | Remote Sensing |
| Subjects: | |
| Online Access: | https://www.mdpi.com/2072-4292/15/3/567 |
| _version_ | 1827759657855221760 |
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| author | Jesús Polo Redlich J. García |
| author_facet | Jesús Polo Redlich J. García |
| author_sort | Jesús Polo |
| collection | DOAJ |
| description | Solar cadasters are excellent tools for determining the most suitable rooftops and areas for PV deployment in urban environments. There are several open models that are available to compute the solar potential in cities. The Solar Energy on Building Envelopes (SEBE) is a powerful model incorporated in a geographic information system (QGIS). The main input for these tools is the digital surface model (DSM). The accuracy of the DSM can contribute significantly to the uncertainty of the solar potential, since it is the basis of the shading and sky view factor computation. This work explores the impact of two different methodologies for creating a DSM to the solar potential. Solar potential is estimated for a small area in a university campus in Madrid using photogrammetry from google imagery and LiDAR data to compute different DSM. Large differences could be observed in the building edges and in the areas with a more complex and diverse topology that resulted in significant differences in the solar potential. The RSMD at a measuring point in the building rooftop can range from 10% to 50% in the evaluation of results. However, the flat and clear areas are much less affected by these differences. A combination of both techniques is suggested as future work to create an accurate DSM. |
| first_indexed | 2024-03-11T09:28:51Z |
| format | Article |
| id | doaj.art-d36cac7dbddb4611b20f0c2170bbe210 |
| institution | Directory Open Access Journal |
| issn | 2072-4292 |
| language | English |
| last_indexed | 2024-03-11T09:28:51Z |
| publishDate | 2023-01-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Remote Sensing |
| spelling | doaj.art-d36cac7dbddb4611b20f0c2170bbe2102023-11-16T17:51:04ZengMDPI AGRemote Sensing2072-42922023-01-0115356710.3390/rs15030567Solar Potential Uncertainty in Building Rooftops as a Function of Digital Surface Model AccuracyJesús Polo0Redlich J. García1Photovoltaic Solar Energy Unit, Renewable Energy Division, CIEMAT, Avda. Complutense 40, 28040 Madrid, SpainDepartment of Mechanical and Metallurgial Engineering, Pontificia Universidad Católica de Chile, Santiago 7820436, ChileSolar cadasters are excellent tools for determining the most suitable rooftops and areas for PV deployment in urban environments. There are several open models that are available to compute the solar potential in cities. The Solar Energy on Building Envelopes (SEBE) is a powerful model incorporated in a geographic information system (QGIS). The main input for these tools is the digital surface model (DSM). The accuracy of the DSM can contribute significantly to the uncertainty of the solar potential, since it is the basis of the shading and sky view factor computation. This work explores the impact of two different methodologies for creating a DSM to the solar potential. Solar potential is estimated for a small area in a university campus in Madrid using photogrammetry from google imagery and LiDAR data to compute different DSM. Large differences could be observed in the building edges and in the areas with a more complex and diverse topology that resulted in significant differences in the solar potential. The RSMD at a measuring point in the building rooftop can range from 10% to 50% in the evaluation of results. However, the flat and clear areas are much less affected by these differences. A combination of both techniques is suggested as future work to create an accurate DSM.https://www.mdpi.com/2072-4292/15/3/567solar cadastersolar potential in rooftopsdigital surface modelgeographic information system |
| spellingShingle | Jesús Polo Redlich J. García Solar Potential Uncertainty in Building Rooftops as a Function of Digital Surface Model Accuracy Remote Sensing solar cadaster solar potential in rooftops digital surface model geographic information system |
| title | Solar Potential Uncertainty in Building Rooftops as a Function of Digital Surface Model Accuracy |
| title_full | Solar Potential Uncertainty in Building Rooftops as a Function of Digital Surface Model Accuracy |
| title_fullStr | Solar Potential Uncertainty in Building Rooftops as a Function of Digital Surface Model Accuracy |
| title_full_unstemmed | Solar Potential Uncertainty in Building Rooftops as a Function of Digital Surface Model Accuracy |
| title_short | Solar Potential Uncertainty in Building Rooftops as a Function of Digital Surface Model Accuracy |
| title_sort | solar potential uncertainty in building rooftops as a function of digital surface model accuracy |
| topic | solar cadaster solar potential in rooftops digital surface model geographic information system |
| url | https://www.mdpi.com/2072-4292/15/3/567 |
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