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docs/examples/shading/plot_martinez_shade_loss.py

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"""
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# %%
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# This example illustrates how to use the work of Martinez et al. [1]_.
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# The model is implemented in :py:func:`pvlib.shading.martinez_shade_loss`.
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# This model corrects the beam and circumsolar incident irradiance
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# This example illustrates how to use the proposed by Martinez et al. [1]_.
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# The model corrects the beam and circumsolar incident irradiance
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# based on the number of shaded *blocks*. A *block* is defined as a
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# group of cells that are protected by a bypass diode.
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# More information on the *blocks* can be found in the original paper [1]_ and
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# in :py:func:`pvlib.shading.martinez_shade_loss` documentation.
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# in :py:func:`pvlib.shading.martinez_shade_factor` documentation.
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#
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# The following key functions are used in this example:
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# 1. :py:func:`pvlib.shading.martinez_shade_loss` to calculate the adjustment
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# 1. :py:func:`pvlib.shading.martinez_shade_factor` to calculate the adjustment
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# factor for the direct irradiance component.
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# 2. :py:func:`pvlib.shading.shaded_fraction1d` to calculate the fraction of
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# shaded surface and consequently the number of shaded *blocks* due to
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#
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# Setting up the system
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# ----------------------
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# Let's start by defining the location and the time range for the analysis.
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# Let's start by defining the system characteristics, location and the time
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# range for the analysis.
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import pvlib
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import pandas as pd
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metadata["latitude"], metadata["longitude"], altitude=metadata["elevation"]
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)
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# Coerce a year: function above returns typical months of different years
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# Coerce a year: function above returns typical months from different years
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pvgis_data.index = [ts.replace(year=2024) for ts in pvgis_data.index]
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# Select day to show
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weather_data = pvgis_data["2024-07-11"]

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