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 (School of Engineering, Architecture and Landscape (hepia), HES-SO // University of Applied Sciences Western Switzerland) ; Carneiro, Claudio (School of Engineering, Architecture and Landscape (hepia), HES-SO // University of Applied Sciences Western Switzerland) ; Camponovo, Reto (School of Engineering, Architecture and Landscape (hepia), HES-SO // University of Applied Sciences Western Switzerland) ; Ineichen, Pierre (Energy Systems, University of Geneva, Geneva, Switzerland) ; Morello, Eugenio (Laboratorio di Simulazione Urbana “Fausto Curti”, Politecnico di Milano, Milano, Italy) ; Boulmier, Anthony (School of Engineering, Architecture and Landscape (hepia), HES-SO // University of Applied Sciences Western Switzerland) ; Abdennadher, Nabil (School of Engineering, Architecture and Landscape (hepia), HES-SO // University of Applied Sciences Western Switzerland) ; Dervey, Sébastien (School of Engineering, HES-SO Valais-Wallis, HEI, HES-SO // University of Applied Sciences Western Switzerland) ; Ellert, Christoph (School of Engineering, HES-SO Valais-Wallis, HEI, HES-SO // University of Applied Sciences Western Switzerland)

The paper presents the core methodology for assessing solar radiation and energy production on building rooftops and vertical facades (still rarely considered) of the inner-city. This integrated tool is based on the use of LiDAR, 2D and 3D cadastral data. Together with solar radiation and astronomical models, it calculates the global irradiance for a set of points located on roofs, ground, and facades. Although the tool takes simultaneously roofs, ground, and facades, different methods of shadow casting are applied. Shadow casting on rooftops is based on image processing techniques. On the other hand, the assessment on facade involves first to create and interpolate points along the facades and then to implement a point-by-point shadow casting routine. The paper is structured in five parts: (i) state of the art on the use of 3D GIS and automated processes in assessing solar radiation in the built environment, (ii) overview on the methodological framework used in the paper, (iii) detailed presentation of the method proposed for solar modeling and shadow casting, in particular by introducing an innovative approach for modeling the sky view factor (SVF), (iv) demonstration of the solar model introduced in this paper through applications in Geneva’s building roofs (solar cadaster) and facades, (v) validation of the solar model in some Geneva’s spots, focusing especially on two distinct comparisons: solar model versus fisheye catchments on partially inclined surfaces (roof component); solar model versus photovoltaic simulation tool PVSyst on vertical surfaces (facades). Concerning the roof component, validation results emphasize global sensitivity related to the density of light sources on the sky vault to model the SVF. The low dense sky model with 145 light sources gives satisfying results, especially when processing solar cadasters in large urban areas, thus allowing to save computation time. In the case of building facades, introducing weighting factor in SVF calculation leads to outputs close to those obtained by PVSyst. Such good validation results make the proposed model a reliable tool to: (i) automatically process solar cadaster on building rooftops and facades at large urban scales and (ii) support solar energy planning and energy transition policies.


Keywords:
Article Type:
scientifique
Faculty:
Ingénierie et Architecture
School:
HEI-VS
HEPIA - Genève
Institute:
inIT - Institut d'Ingénierie Informatique et des Télécommunications
inPACT - Institut du Paysage, d'Architecture, de la Construction et du Territoire
Institut Systèmes industriels
Subject(s):
Ingénierie
Date:
2018
Pagination:
22 p.
Published in:
Frontiers in Built Environment
Numeration (vol. no.):
2018, 4, 14
DOI:
Appears in Collection:



 Record created 2018-08-07, last modified 2018-12-20

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