TMY tutorial

This tutorial shows how to use the pvlib.tmy module to read data from TMY2 and TMY3 files.

This tutorial has been tested against the following package versions:

pvlib 0.2.1
Python 2.7.10
IPython 3.2
pandas 0.16.2

Authors:

Will Holmgren (@wholmgren), University of Arizona. July 2014, July 2015.

Import modules



In [1]:

    
# built in python modules
import datetime
import os
import inspect

# python add-ons
import numpy as np
import pandas as pd

# plotting libraries
%matplotlib inline
import matplotlib.pyplot as plt
try:
    import seaborn as sns
except ImportError:
    pass

import pvlib

pvlib comes packaged with a TMY2 and a TMY3 data file.



In [2]:

    
# Find the absolute file path to your pvlib installation
pvlib_abspath = os.path.dirname(os.path.abspath(inspect.getfile(pvlib)))

Import the TMY data using the functions in the pvlib.tmy module.



In [3]:

    
tmy3_data, tmy3_metadata = pvlib.tmy.readtmy3(os.path.join(pvlib_abspath, 'data', '703165TY.csv'))
tmy2_data, tmy2_metadata = pvlib.tmy.readtmy2(os.path.join(pvlib_abspath, 'data', '12839.tm2'))

Print the TMY3 metadata and the first 5 lines of the data.



In [4]:

    
print(tmy3_metadata)
tmy3_data.head(5)









    



{'TZ': -9.0, 'Name': '"SAND POINT"', 'altitude': 7.0, 'USAF': 703165, 'longitude': -160.517, 'State': 'AK', 'latitude': 55.317}






    Out[4]:






  
    
      
      ETR
      ETRN
      GHI
      GHISource
      GHIUncertainty
      DNI
      DNISource
      DNIUncertainty
      DHI
      DHISource
      ...
      AOD
      AODSource
      AODUncertainty
      Alb
      AlbSource
      AlbUncertainty
      Lprecipdepth
      Lprecipquantity
      LprecipSource
      LprecipUncertainty
    
    
      datetime
      
      
      
      
      
      
      
      
      
      
      
      
      
      
      
      
      
      
      
      
      
    
  
  
    
      1997-01-01 01:00:00-09:00
      0
      0
      0
      1
      0
      0
      1
      0
      0
      1
      ...
      0.051
      F
      8
      0.24
      F
      8
      -9900
      -9900
      ?
      0
    
    
      1997-01-01 02:00:00-09:00
      0
      0
      0
      1
      0
      0
      1
      0
      0
      1
      ...
      0.051
      F
      8
      0.24
      F
      8
      -9900
      -9900
      ?
      0
    
    
      1997-01-01 03:00:00-09:00
      0
      0
      0
      1
      0
      0
      1
      0
      0
      1
      ...
      0.051
      F
      8
      0.24
      F
      8
      -9900
      -9900
      ?
      0
    
    
      1997-01-01 04:00:00-09:00
      0
      0
      0
      1
      0
      0
      1
      0
      0
      1
      ...
      0.051
      F
      8
      0.24
      F
      8
      -9900
      -9900
      ?
      0
    
    
      1997-01-01 05:00:00-09:00
      0
      0
      0
      1
      0
      0
      1
      0
      0
      1
      ...
      0.051
      F
      8
      0.24
      F
      8
      -9900
      -9900
      ?
      0
    
  

5 rows × 66 columns



In [5]:

    
tmy3_data['GHI'].plot()









    Out[5]:





<matplotlib.axes._subplots.AxesSubplot at 0x7f8056b33850>

The TMY readers have an optional argument to coerce the year to a single value.



In [6]:

    
tmy3_data, tmy3_metadata = pvlib.tmy.readtmy3(os.path.join(pvlib_abspath, 'data', '703165TY.csv'), coerce_year=1987)



In [7]:

    
tmy3_data['GHI'].plot()









    Out[7]:





<matplotlib.axes._subplots.AxesSubplot at 0x7f8056513190>

Here's the TMY2 data.



In [8]:

    
print(tmy2_metadata)
print(tmy2_data.head())









    



{'City': 'MIAMI', 'TZ': -5, 'altitude': 2.0, 'longitude': -80.26666666666667, 'State': 'FL', 'WBAN': '12839', 'latitude': 25.8}
                           year  month  day  hour  ETR  ETRN  GHI GHISource  \
1962-01-01 00:00:00-05:00    62      1    1     1    0     0    0         ?   
1962-01-01 01:00:00-05:00    62      1    1     2    0     0    0         ?   
1962-01-01 02:00:00-05:00    62      1    1     3    0     0    0         ?   
1962-01-01 03:00:00-05:00    62      1    1     4    0     0    0         ?   
1962-01-01 04:00:00-05:00    62      1    1     5    0     0    0         ?   

                           GHIUncertainty  DNI          ...            \
1962-01-01 00:00:00-05:00               0    0          ...             
1962-01-01 01:00:00-05:00               0    0          ...             
1962-01-01 02:00:00-05:00               0    0          ...             
1962-01-01 03:00:00-05:00               0    0          ...             
1962-01-01 04:00:00-05:00               0    0          ...             

                          PwatUncertainty  AOD  AODSource AODUncertainty  \
1962-01-01 00:00:00-05:00               8   62          F              8   
1962-01-01 01:00:00-05:00               8   62          F              8   
1962-01-01 02:00:00-05:00               8   62          F              8   
1962-01-01 03:00:00-05:00               8   62          F              8   
1962-01-01 04:00:00-05:00               8   62          F              8   

                           SnowDepth  SnowDepthSource SnowDepthUncertainty  \
1962-01-01 00:00:00-05:00          0                A                    7   
1962-01-01 01:00:00-05:00          0                A                    7   
1962-01-01 02:00:00-05:00          0                A                    7   
1962-01-01 03:00:00-05:00          0                A                    7   
1962-01-01 04:00:00-05:00          0                A                    7   

                           LastSnowfall  LastSnowfallSource  \
1962-01-01 00:00:00-05:00            88                   E   
1962-01-01 01:00:00-05:00            88                   E   
1962-01-01 02:00:00-05:00            88                   E   
1962-01-01 03:00:00-05:00            88                   E   
1962-01-01 04:00:00-05:00            88                   E   

                          LastSnowfallUncertaint  
1962-01-01 00:00:00-05:00                      7  
1962-01-01 01:00:00-05:00                      7  
1962-01-01 02:00:00-05:00                      7  
1962-01-01 03:00:00-05:00                      7  
1962-01-01 04:00:00-05:00                      7  

[5 rows x 70 columns]

Finally, the TMY readers can access TMY files directly from the NREL website.



In [9]:

    
tmy3_data, tmy3_metadata = pvlib.tmy.readtmy3('http://rredc.nrel.gov/solar/old_data/nsrdb/1991-2005/data/tmy3/722740TYA.CSV', coerce_year=2015)



In [10]:

    
tmy3_data['GHI'].plot(figsize=(12,6))
plt.title('Tucson TMY GHI')









    Out[10]:





<matplotlib.text.Text at 0x7f80564e8790>



In [ ]:

	ETR	ETRN	GHI	GHISource	GHIUncertainty	DNI	DNISource	DNIUncertainty	DHI	DHISource	...	AOD	AODSource	AODUncertainty	Alb	AlbSource	AlbUncertainty	Lprecipdepth	Lprecipquantity	LprecipSource	LprecipUncertainty
datetime
1997-01-01 01:00:00-09:00	0	0	0	1	0	0	1	0	0	1	...	0.051	F	8	0.24	F	8	-9900	-9900	?	0
1997-01-01 02:00:00-09:00	0	0	0	1	0	0	1	0	0	1	...	0.051	F	8	0.24	F	8	-9900	-9900	?	0
1997-01-01 03:00:00-09:00	0	0	0	1	0	0	1	0	0	1	...	0.051	F	8	0.24	F	8	-9900	-9900	?	0
1997-01-01 04:00:00-09:00	0	0	0	1	0	0	1	0	0	1	...	0.051	F	8	0.24	F	8	-9900	-9900	?	0
1997-01-01 05:00:00-09:00	0	0	0	1	0	0	1	0	0	1	...	0.051	F	8	0.24	F	8	-9900	-9900	?	0