2.7 Surface regeneration 
Only the surfaces where at least one subdivided triangle is 
shadowed are considered for surface regeneration. This step is 
only necessary when a visual output for real time shadow is 
required for an instance of time. If the calculation is carried out 
for any longer time period like and hourly or minutely shadow 
calculation then this step might be excluded. Neighbouring 
subdivided triangles with same shadow status are joined 
together to form shadow and non-shadow region. These regions 
are further merged with other neighbouring region with similar 
shadow status. 
The whole process produces result for an instance of time. To 
get hourly or minutely shadow calculation this has been 
repeatedly applied and the result has been presented in a tabular 
form. 
3. IMPLEMENTATION 
To implement this method a specific area in Germany was 
considered. Former military area Scharnhauser Park shown in 
Figure 3 is an urban conversion and development area of 150 
hectors in the community of Ostfildern on the southern border 
near Stuttgart with 7000 inhabitants. About 80% heating energy 
demand of the whole area is supplied by renewable energies and 
a small portion of electricity is delivered by existing roof top 
photovoltaic system (Tereci et al, 2009). This has been selected 
as the study area for this research because of availability 
CityGML and LIDAR data, building footprints and existing 
photovoltaic cells on roofs and façades. Two types of data have 
been considered for this research, CityGML and LIDAR for 
accuracy. Line plane intersection method has been used initially 
for direct radiation. LIDAR points are suitable for selecting 
points on a surface from which the suns direction represents the 
line. For CityGML data these points needs to be extracted using 
surface subdivision and triangulation. But planes are 
represented by facesets in CityGML, which is also need for the 
algorithm. LIDAR points are needed to be converted into planes 
using surface reconstruction. So, both types of data are potential 
for this research. 
  
Figure 3. Residential area Scharnhauser Park (Eicker et al, 
2010) 
An existing method for photovoltaic potentiality analysis which 
doesn’t consider shadow has been selected as a starting point. 
Solarcity3D is a student project from University of Applied 
Sciences Stuttgart. This is a Software Interface for the 
calculation and visualization of photovoltaic potential in city 
areas. It connects 3D city models and simulation engines for the 
calculation and visualization of potential energy yields. 
Parameters considered here are geographical position and 
    
orientation, roof area and pitch, climate conditions etc 
(Solarcity3D, 2009). This will be modified and fast and exact 
shadow detection method will be added and effect will be 
determined during this research as well as the guideline for 
minimum quality of data required for the calculation will also 
be prepared.SolarCity3D is the base of this research so the 
shadow calculation has been integrated with its system 
architecture. 
  
3D Viewer CATsEyE 
INSEL CSV l ! 
Simulation s 
Engine »| SolarCity3D CSV = Shadow 
= Calculation 
heer 
: : : 
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
Sim 
results CATS 
LT ER 
EXCEL 3D urban model | | ——— 
{City GML) Ë Spatial DB 
Es i (MySQL) 
= el 
Le "EE A e 
Figure 4. System Architecture (Alam et al, 2011) 
For shadow calculation geometrical information is needed as 
input and semantic information serves the simulation tool. 
Citymodel Administration Toolkit (CAT3D) has been used, to 
handle, manage and merge different formats of 3D Geodata, 
DBMS, and data schema on the server side. It provides data in 
different layers, which can group objects thematically for clients 
to query models according to needs. CAT3D framework is 
divided into four parts: Data Connectors, Data Format Creators, 
Data Mapping and Utilities (Knapp et al, 2007). Shadow 
calculator gets the information from CAT3D framework and 
performs shadow calculation at specified time interval (per day, 
hour, minute) and prepares a CSV file with shadow information 
for each building. This file is feed into the SolarCity3D for solar 
potentiality analysis with the simulation engine INSEL. A 3D 
viewer is used for classified visualization of the results. And the 
final potentiality result with shadow consideration is also 
presented in excel file. Figure 4 represents the whole system 
architecture. 
4. RESULT & ANALYSIS 
Initially to check the algorithm a test model with two buildings 
as shown in Figure 5, have been tested one of which has a 
photovoltaic module on its roof. 
  
  
Figure 5. Implementation on a test model 
The model has been tested for each hour of the year, which 
means 8760 times. The test has given correct tabular result 
      
    
   
   
   
     
   
  
   
    
    
    
   
    
   
   
   
   
   
   
   
   
   
   
   
   
   
    
  
    
   
    
    
  
  
    
    
    
   
  
  
    
   
     
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