5. CONCLUSION AND FUTURE WORK
A general research challenge has been introduced for using 3D
city models to estimate shadow effect in solar potentiality
analysis. The parameters for photovoltaic energy prediction,
solar energy parameters and facts have also been mentioned.
We have discussed about technologies involved to represent 3D
city models. The test implementation on a study area for beam
radiation has also been presented. Future work of this research
will focus on detection of diffuse radiation, impact of reflection,
utilization of programmable rendering pipeline of modern
graphics hardware or GPU. This research will also focus the
data quality of 3D city models and LIDAR point clouds, which
is minimum for solar energy potentiality estimation. Future
work of this research also includes development of soft shadow
algorithm will consider the indirect radiation also. When the
sun is blocked by any obstacle, only the direct radiation is
blocked but it doesn't get completely dark. Then exact shadow
algorithm will be developed for both hard and soft shadow and
also reflectance, texture, color of surrounding objects. This will
represent the real life shadow impression. Quality of data plays
a vital role in this research. There will always be a limit to what
extent the building information as well as neighbouring object
information can be extracted. The emphasis of next part of
research work would be to prepare a suggestion or a guideline
of which kind of data have influence on the photovoltaic output.
Finally a demo version of the shadow simulator will be
prepared. This will provide a service to calculate real time
shadow as well as total and average shadow to feed in to the
photovoltaic potentiality simulator and also as an output data.
REFERENCE
References from Journals:
Cascone, Y., Corrado. V & Sera, V., 2011. Calculation
procedure of the shading factor under complex boundary
conditions. Solar Energy, 85(10), pp. 2524-2539.
Hofierka, J. & Kañuk, J., 2009. Assessment of photovoltaic
potential in urban areas using open-source solar radiation tools.
Renewable Energy, 34(10), pp. 2206-2214.
Izquierdo, S., Rodrigues, M. & Fueyo, N., 2008. A method for
estimating the geographical distribution of the available roof
surface area for large-scale photovoltaic energy-potential
evaluations. Solar Energy, 82(10), pp. 929-939.
Joachem, A., Hoefle, B., Rutzinger, M. & Pfeifer, N., 2009.
Automatic roof plane detection and analysis in airborne LIDAR
point clouds for solar potential assessment. Sensors, 9(7), pp.
5241-5262.
References from Other Literature:
Alam, N., Coors, V, Zlatanova, S. & Oosterom, P., 2011.
Shadow effect on photovoltaic potentiality analysis using 3D
city models. In: Proceedings of the Joint ISPRS Workshop on
3D City Modelling& Applications and the 6th 3D Geolnfo
Conference, 26-28 June, 2011, Wuhan, China.
Eicker, U., Strzalka, A., Schulte, C. Bogdahn, J., Schumacher,
J., Coors, V., 2010. Large Scale Integration of Photovoltaic in
Cities ICSU 2010, 1st International Conference on Sustainable
Urbanization, 15-17 December 2010, Hong Kong, China
Schumacher, J., 1991. Digitale Simulation regenerativer
elektrischer Energieversorgungssysteme, Dissertation,
Universität Oldenburg, Oldenburg, Germany.
SolarCity3D, 2009. Solar Potential Calculation and
Visualization based on 3D CityModels. [Poster]. Stuttgart :
HFT Stuttgart, 2009. Student Project.
Tereci, A., Schneider, D., Kesten, D., Strzalka, A. & Eicker, U.,
2009. Energy Saving Potential and Eco-nomical Analysis of
Solar Systems in the Urban Quarter Scharnhauser Park, ISES
Solar World Congress, Renewable Energy Shaping Our Future.
11-14 October 2009Johannesburg, South Africa.
References from websites:
Baum, I. V., 2009. Documentation on Dr. Baum Research e.K.
“Shadow Analyzer”, Schwäbisch Hall, Germany.
http://www.drbaumresearch.com/prod38.htm. (11 Dec. 2010)
Waserrab, J., 2011. Report on Deutsche Welle “Germany’s
solar industry loses its shine", Bonn, Germany.
http://www.dw-world.de/dw/article/0,,15423618,00.html (29
Sep. 2011)
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