This paper shows the results of a research on parametric geometric transformation of the building volume and transformations of facade surfaces to optimize solar access of buildings in an existing urban district. Photovoltaic systems are generally installed on roof tops of buildings located in low density areas due to the availability of horizontal surfaces, but the developments of cities with tall buildings and the lack of available horizontal surfaces have encouraged photovoltaic integration on facades. The new policies of regulations to contain the horizontal city’s development and to increase the use of renewable resources suggest a conscious and responsible design process. Within this scenario the main aim of this study is to find the way to improve solar energy capture in the urban existing context. The study wants to localize the best areas on the facade surfaces to install the solar systems and optimize the solar energy production in order to cover a part of energy demands. The optimization process starts from a simple three-dimensional volumetric modelling, with fixed parameters (height, floor area and volume of the building). Then facade surfaces are manipulated in an iterative parametric design process to evaluate the solar radiation of different geometric transformations using a generative digital modelling software (Rhynoceros + Grasshopper) and solar dynamic simulation tool (Radiance/Daysim). The proposed method is restricted to the relationship between solar access and solar applications, but the further development of the research aims investigate the mutual effects among neighbouring buildings in term of solar reflections and increase of superficial temperatures. The global process has been validated through a case study, analysing a typical development in Milan, involving the demolition of an existing building and the reconstruction of the same volume, with a solar optimized shape.
[1]
Manfred Hegger,et al.
Energy Manual: Sustainable Architecture
,
2008
.
[2]
Stephen Carpenter,et al.
Learning from Experiences with Advanced Houses of the World
,
1995
.
[3]
Peter J. Bentley,et al.
Evolutionary Design By Computers
,
1999
.
[4]
Peter Lund,et al.
Multivariate optimization of design trade-offs for solar low energy buildings
,
1999
.
[5]
R. Compagnon.
Solar and daylight availability in the urban fabric
,
2004
.
[6]
Gabriele Lobaccaro,et al.
Solar districts: design strategies to exploit the solar potential of urban areas
,
2012
.
[7]
Gabriele Lobaccaro,et al.
District Geometry Simulation: A Study for the Optimization of Solar Façades in Urban Canopy Layers☆
,
2012
.
[8]
Christoph F. Reinhart,et al.
Standard daylight coefficient model for dynamic daylighting simulations
,
2008
.
[9]
Christoph F. Reinhart,et al.
Validation of dynamic RADIANCE-based daylight simulations for a test office with external blinds
,
2001
.
[10]
Ahmet Arisoy,et al.
Solar energy potential for heating and cooling systems in big cities of Turkey
,
2002
.
[11]
C. Reinhart,et al.
Development and validation of a Radiance model for a translucent panel
,
2006
.
[12]
Christoph F. Reinhart,et al.
SOLAR AVAILABILITY: A COMPARISON STUDY OF SIX IRRADIATION DISTRIBUTION METHODS
,
2011
.
[13]
K. Gopinathan.
Solar radiation on variously oriented sloping surfaces
,
1991
.