In [13]:

    

%load_ext autoreload
%autoreload 2
%matplotlib inline

from smarts import *
import matplotlib.pyplot as plt
import numpy as np
import pandas as pd

from pypvcell.solarcell import SQCell,MJCell


    

    




The autoreload extension is already loaded. To reload it, use:
  %reload_ext autoreload

In [36]:

    

times=pd.date_range(start='2016-12-01 04:00',end='2016-12-10 23:00',freq='15T',tz='Japan')
df=get_clear_sky(times)
print(df.head())


    

    




                           WVLGTH  ET_SPCTRUM   BEAM_NORMAL    BEAM_NORM+  \
time                                                                        
2016-12-01 06:45:00+09:00   300.0      0.5200  7.466000e-28  7.466000e-28   
2016-12-01 06:45:00+09:00   302.0      0.5468  2.534000e-26  2.534000e-26   
2016-12-01 06:45:00+09:00   304.0      0.5871  5.658000e-25  5.658000e-25   
2016-12-01 06:45:00+09:00   306.0      0.6154  9.159000e-24  9.159000e-24   
2016-12-01 06:45:00+09:00   308.0      0.6337  1.124000e-22  1.124000e-22   

                             GLOB_HORIZ    GLOBL_TILT  
time                                                   
2016-12-01 06:45:00+09:00  5.630000e-07  5.085000e-07  
2016-12-01 06:45:00+09:00  1.425000e-06  1.287000e-06  
2016-12-01 06:45:00+09:00  3.593000e-06  3.246000e-06  
2016-12-01 06:45:00+09:00  8.195000e-06  7.404000e-06  
2016-12-01 06:45:00+09:00  1.621000e-05  1.465000e-05  

In [37]:

    

df.to_hdf('store_tl.h5',key='df',mode='w')


    

In [47]:

    

ndf=pd.read_hdf('store_tl.h5')
df=ndf


    

In [48]:

    

# Set up a basic solar cells
ingap_cell=SQCell(1.9,297,rad_eta=0.001)
gaas_cell=SQCell(1.42,297,rad_eta=0.01)

si_cell=SQCell(1.12,297,rad_eta=0.001)
si_cell.set_description("Si")

future_si_cell=SQCell(1.12,297,rad_eta=0.01)
future_si_cell.set_description("future Si")

future_backplane_cell=SQCell(1.42,297,rad_eta=0.01)
future_backplane_cell.set_description("fp-GaAs")

ge_cell=SQCell(0.67,297,rad_eta=0.0001)
one_ev_cell=SQCell(1.0,297,rad_eta=1e-5)

twoj_cell=MJCell([ingap_cell,gaas_cell])
twoj_cell.set_description("2J")
threej_cell=MJCell([ingap_cell,gaas_cell,ge_cell])
threej_cell.set_description("3J")

fourj_cell=MJCell([ingap_cell,gaas_cell,one_ev_cell,ge_cell])
fourj_cell.set_description("4J")


    

In [49]:

    

# some of the time index does not have sun spectrum because azimuthal angle < , we need to filter out this
new_time=pd.unique(df.index)


    

In [50]:

    

new_time


    

    
Out[50]:





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       '2016-12-10T07:30:00.000000000'], dtype='datetime64[ns]')

In [51]:

    

df.loc[new_time[5],:].head()


    

    
Out[51]:






  

    

      

      
WVLGTH
      
ET_SPCTRUM
      
BEAM_NORMAL
      
BEAM_NORM+
      
GLOB_HORIZ
      
GLOBL_TILT
    
    

      
time
      

      

      

      

      

      

    
  
  

    

      
2016-12-01 08:00:00+09:00
      
300.0
      
0.5200
      
2.564000e-07
      
2.647000e-07
      
0.000024
      
0.000022
    
    

      
2016-12-01 08:00:00+09:00
      
302.0
      
0.5468
      
1.435000e-06
      
1.481000e-06
      
0.000077
      
0.000070
    
    

      
2016-12-01 08:00:00+09:00
      
304.0
      
0.5871
      
6.378000e-06
      
6.579000e-06
      
0.000219
      
0.000200
    
    

      
2016-12-01 08:00:00+09:00
      
306.0
      
0.6154
      
2.330000e-05
      
2.402000e-05
      
0.000577
      
0.000530
    
    

      
2016-12-01 08:00:00+09:00
      
308.0
      
0.6337
      
7.113000e-05
      
7.330000e-05
      
0.001376
      
0.001267
    
  

In [52]:

    

plot_df=df.loc[new_time[10],:]
plt.plot(plot_df['WVLGTH'],plot_df['GLOB_HORIZ'])


    

    
Out[52]:





[<matplotlib.lines.Line2D at 0x10c339c50>]






    

In [53]:

    

eta_array=[]
test_cell=fourj_cell
for t in new_time:
    time_spec=df.loc[t,:]
    spec_d=spec_data_to_spec_class(time_spec)
    ill=spec_d['direct_exp']
    test_cell.set_input_spectrum(ill)
    eta=test_cell.get_eta()
    eta_array.append(eta)

eta_array=np.array(eta_array)
plt.plot(new_time,eta_array)


    

    
Out[53]:





[<matplotlib.lines.Line2D at 0x10c3fcef0>]






    

In [54]:

    

eta_array=[]
test_cell=threej_cell
for t in new_time:
    time_spec=df.loc[t,:]
    spec_d=spec_data_to_spec_class(time_spec)
    ill=spec_d['direct_exp']
    test_cell.set_input_spectrum(ill)
    eta=test_cell.get_eta()
    eta_array.append(eta)

eta_array=np.array(eta_array)
plt.plot(new_time,eta_array)


    

    
Out[54]:





[<matplotlib.lines.Line2D at 0x10ceda9b0>]






    

In [55]:

    

eta_array=[]
test_cell=twoj_cell
for t in new_time:
    time_spec=df.loc[t,:]
    spec_d=spec_data_to_spec_class(time_spec)
    ill=spec_d['direct_exp']
    test_cell.set_input_spectrum(ill)
    eta=test_cell.get_eta()
    eta_array.append(eta)

eta_array=np.array(eta_array)
plt.plot(new_time,eta_array)


    

    
Out[55]:





[<matplotlib.lines.Line2D at 0x10ced7f28>]






    

In [56]:

    

eta_array=[]
test_cell=si_cell
for t in new_time:
    time_spec=df.loc[t,:]
    spec_d=spec_data_to_spec_class(time_spec)
    ill=spec_d['direct_exp']
    test_cell.set_input_spectrum(ill)
    eta=test_cell.get_eta()
    eta_array.append(eta)

eta_array=np.array(eta_array)
plt.plot(new_time,eta_array)


    

    
Out[56]:





[<matplotlib.lines.Line2D at 0x10d0a3fd0>]






    

In [ ]:

    




    

In [ ]: