Solar Energy Potential Assessment on Rooftops and Facades in Large Built Environments Based on LiDAR Data, Image Processing, and Cloud Computing. Methodological Background, Application, and Validation in Geneva (Solar Cadaster)

Desthieux, Gilles; Carneiro, Claudio; Camponovo, Reto; Ineichen, Pierre; Morello, Eugenio; Boulmier, Anthony; Abdennadher, Nabil; Dervey, Sébastien; Ellert, Christoph

doi:10.3389/fbuil.2018.00014

Cited by 75 publications

(67 citation statements)

References 29 publications

(43 reference statements)

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“…Our previous work on solar modelling and mapping in a built environment [10][11][12] was for the Solar Cadaster of the canton of Geneva.…”

Section: Previous Related Workmentioning

confidence: 99%

“…This trans-border region has an area of about 2000 km 2 and contains nearly one million inhabitants, with Geneva as the main city in the middle. A first solar cadaster was developed for the Canton of Geneva only (280 km 2 ), as presented in Desthieux et al [10]. The goal now is to update and extend this solar cadaster for the whole of Greater Geneva area, with the aim of intensifying solar energy production.…”

Section: Introductionmentioning

confidence: 99%

“…Irradiation computation uses meteorological data from Meteonorm ® , which gives statistical and representative data on global, diffuse, and direct irradiation on horizontal surfaces for a given location like Geneva Airport in the context of the solar cadaster. In order to save computation time, hourly data were averaged by month and a representative day of each month (around the 15th of the month) was chosen for the solar geometry as introduced by [10]. Irradiation is the result of the image processing step.…”

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confidence: 99%

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GPU-Enabled Shadow Casting for Solar Potential Estimation in Large Urban Areas. Application to the Solar Cadaster of Greater Geneva

et al. 2020

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In the context of encouraging the development of renewable energy, this paper deals with the description of a software solution for mapping out solar potential in a large scale and in high resolution. We leverage the performance provided by Graphics Processing Units (GPUs) to accelerate shadow casting procedures (used both for direct sunlight exposure and the sky view factor), as well as use off-the-shelf components to compute an average weather pattern for a given area. Application of the approach is presented in the context of the solar cadaster of Greater Geneva (2000 km2). The results show that doing the analysis on a square tile of 3.4 km at a resolution of 0.5 m takes up to two hours, which is better than what we were achieving with the previous work. This shows that GPU-based calculations are highly competitive in the field of solar potential modeling.

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“…Our previous work on solar modelling and mapping in a built environment [10][11][12] was for the Solar Cadaster of the canton of Geneva.…”

Section: Previous Related Workmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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confidence: 99%

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GPU-Enabled Shadow Casting for Solar Potential Estimation in Large Urban Areas. Application to the Solar Cadaster of Greater Geneva

et al. 2020

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“…Specifically, trees and overhanging building structures cannot be correctly modeled where each xy-position is only represented by a single elevation (Fogl, Moudrý, 2016). Correctly modeling non-rectilinear façades is also difficult without specific workarounds (Catita et al, 2014;Desthieux et al, 2018). Apart from the aforementioned raster input, laser scanning based 3D vector models have also been used for solar potential analysis (e.g.…”

Section: Related Workmentioning

confidence: 99%

A Big Data Approach for Comprehensive Urban Shadow Analysis From Airborne Laser Scanning Point Clouds

Laefer

2019

ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci.

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<p><strong>Abstract.</strong> Because of the importance of access to sunlight, shadow analysis is a common consideration in urban design, especially for dense urban developments. As shadow computation is computationally expensive, most urban shadow analysis tools have to date circumvented the high computational costs by representing urban complexity only through simplified geometric models. The simplification process removes details and adversely affects the level of realism of the ultimate results. In this paper, an alternative approach is presented by utilizing the highest level of detail and resolution captured in the geometric input data source, which is an extremely high-resolution airborne laser scanning point cloud (300 points/m2). To cope with the high computational demand caused by the use of this dense and detailed input data set, the Comprehensive Urban Shadow algorithm is introduced to distribute the computation for parallel processing on a Hadoop cluster. The proposed comprehensive urban shadow analysis solution is scalable, reasonably fast, and capable of preserving the original resolution and geometric detail of the original point cloud data.</p>

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“…Furthermore, municipalities should adopt support planning instruments to optimize the use of solar energy potential through orientation, angle, irradiation, and solar energy generation from solar systems architecturally integrated on roofs, façades, and other relevant locations (e.g., parking shelters). In this scenario, solar mapping of urban surfaces is shown as a promising approach worldwide [9][10][11]. However, the analysis of the most recent existing methodologies for solar maps in Europe (Section 2.1) allowed individualization of the existing research gaps to assess solar energy potential at the neighborhood scale.…”

Section: Introductionmentioning

confidence: 99%

A Methodological Analysis Approach to Assess Solar Energy Potential at the Neighborhood Scale

et al. 2019

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Rapid and uncontrolled urbanization is continuously increasing buildings’ energy consumption and greenhouse gas emissions into the atmosphere. In this scenario, solar energy integrated into the built environment can play an important role in optimizing the use of renewable energy sources on urban surfaces. Preliminary solar analyses to map the solar accessibility and solar potential of building surfaces (roofs and façades) should become a common practice among urban planners, architects, and public authorities. This paper presents an approach to support urban actors to assess solar energy potential at the neighborhood scale and to address the use of solar energy by considering overshadowing effects and solar inter-building reflections in accordance with urban morphology and building characteristics. The approach starts with urban analysis and solar irradiation analysis to elaborate solar mapping of façades and roofs. Data processing allows assessment of the solar potential of the whole case study neighborhood of Sluppen in Trondheim (Norway) by localizing the most radiated parts of buildings’ surfaces. Reduction factors defined by a new method are used to estimate the final solar potential considering shadowing caused by the presence of buildings’ architectural elements (e.g., glazed surfaces, balconies, external staircases, projections) and self-shading. Finally, rough estimation of solar energy generation is assessed by providing preliminary recommendations for solar photovoltaic (PV) systems suited to local conditions. Results show that depending on urban morphology and buildings’ shapes, PV systems can cover more than 40% of the total buildings’ energy needs in Trondheim.

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Solar Energy Potential Assessment on Rooftops and Facades in Large Built Environments Based on LiDAR Data, Image Processing, and Cloud Computing. Methodological Background, Application, and Validation in Geneva (Solar Cadaster)

Cited by 75 publications

References 29 publications

GPU-Enabled Shadow Casting for Solar Potential Estimation in Large Urban Areas. Application to the Solar Cadaster of Greater Geneva

GPU-Enabled Shadow Casting for Solar Potential Estimation in Large Urban Areas. Application to the Solar Cadaster of Greater Geneva

A Big Data Approach for Comprehensive Urban Shadow Analysis From Airborne Laser Scanning Point Clouds

A Methodological Analysis Approach to Assess Solar Energy Potential at the Neighborhood Scale

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