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  4. 3D Model for Solar Energy Potential on Buildings from Urban LiDAR Data
 
conference paper not in proceedings

3D Model for Solar Energy Potential on Buildings from Urban LiDAR Data

Bill, Andreas
•
Mohajeri, Nahid  
•
Scartezzini, Jean-Louis  
2016
UDMV 2016 - Eurographics Workshop on Urban Data Modelling and Visualisation

One of the most promising sustainable energy that can be considered in urban environment is solar energy. A 3D model for solar energy potential on building envelope based on urban LiDAR data was developed in this study. The developed algorithm can be used to model solar irradiation with high spatio-temporal resolution for roofs, facades, and ground surfaces simultaneously based on urban LiDAR data taking into account the vegetation. Global solar irradiation was then obtained for each point on the buildings and ground surfaces with a spatial resolution of 1m2 and a time resolution of 1 hour. The algorithm has been implemented in Matlab and the results were generated for two different test areas in the city of Geneva in Switzerland. The results show that even in a dense urban area, the upper parts of south-east to south-west oriented facades receive 600 to 1000 kWh/m2/year of solar input which is suitable for active solar installations. The results also show that south oriented facades can get higher solar input during winter months than the low inclined roof surfaces. This shows facades have a significant impact on the solar potential of buildings in an urban area, particularly for a sustainable energy planning application.

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Type
conference paper not in proceedings
Author(s)
Bill, Andreas
Mohajeri, Nahid  
Scartezzini, Jean-Louis  
Date Issued

2016

Publisher

The Eurographics Association 2016

Subjects

solar energy

•

urban Lidar data

•

3D model

Editorial or Peer reviewed

REVIEWED

Written at

EPFL

EPFL units
LESO-PB  
Event nameEvent placeEvent date
UDMV 2016 - Eurographics Workshop on Urban Data Modelling and Visualisation

Liège, Belgium

December 8, 2016

Available on Infoscience
December 3, 2016
Use this identifier to reference this record
https://infoscience.epfl.ch/handle/20.500.14299/131732
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