|
10 | 10 | # This example demonstrates how to use diffuse fraction estimation methods to
|
11 | 11 | # obtain direct and diffuse components from measured global horizontal
|
12 | 12 | # irradiance (GHI). Irradiance sensors such as pyranometers typically only
|
13 |
| -# measure GHI. pvlib provides several functions that can be used |
14 |
| -# to separate GHI into the diffuse and direct components. The separate |
15 |
| -# components are needed to estimate the total irradiance on a tilted |
16 |
| -# surface. |
| 13 | +# measure GHI. pvlib provides several functions that can be used to separate |
| 14 | +# GHI into the diffuse and direct components. The separate components are |
| 15 | +# needed to estimate the total irradiance on a tilted surface. |
17 | 16 |
|
18 | 17 | import pathlib
|
19 | 18 | from matplotlib import pyplot as plt
|
|
38 | 37 | longitude=metadata['longitude'], altitude=metadata['altitude'],
|
39 | 38 | pressure=greensboro.Pressure*100, temperature=greensboro.DryBulb)
|
40 | 39 |
|
| 40 | +# %% |
| 41 | +# Methods for separating DHI into diffuse and direct components include: |
| 42 | +# **DISC**, **DIRINT**, **Erbs** and **Boland**. |
| 43 | + |
41 | 44 | # %%
|
42 | 45 | # DISC
|
43 | 46 | # ----
|
|
112 | 115 | greensboro.DHI, out_disc.dhi_disc, out_dirint.dhi_dirint,
|
113 | 116 | out_erbs.dhi_erbs, out_boland.dhi_boland]
|
114 | 117 | dhi = pd.concat(dhi, axis=1).rename(columns=dhi_renames)
|
115 |
| -ghi_kt = pd.concat([greensboro.GHI/1000.0, out_erbs.kt], axis=1) |
| 118 | +ghi_kt = pd.concat([greensboro.GHI/1367.0, out_erbs.kt], axis=1) |
116 | 119 |
|
117 | 120 | # %%
|
118 | 121 | # Finally, let's plot them for a few winter days and compare
|
|
0 commit comments