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Update mismatch_modifiers.ipynb
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‎docs/tutorials/mismatch_modifiers.ipynb

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},
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{
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"cell_type": "code",
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"execution_count": 1,
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"execution_count": null,
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"metadata": {},
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"outputs": [],
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"source": [
@@ -37,6 +37,7 @@
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"import matplotlib.pyplot as plt\n",
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"\n",
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"import pandas as pd\n",
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"import numpy as np\n",
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"\n",
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"# And pvlib\n",
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"import pvlib"
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"### N. Martin & J. M. Ruiz Experimental Mismatch Modifier\n",
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"### N. Martin & J. M. Ruiz Mismatch Modifier\n",
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"This modifier takes into account the responsivities to different spectrums,\n",
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"characterized by the airmass and the clearness index, as two independent\n",
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"variables. In fact, it is 3 different modifiers, each one for each component\n",
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"(``poa_direct``, ``poa_sky_diffuse``, ``poa_ground_diffuse``)\n",
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"\n",
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"The formula for each component has three coefficients; we are lucky the authors\n",
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"of this model computed fitting values for m-Si, p-Si and a-Si!\n",
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"However, if you would like to compute and/or use your own values, keep reading."
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"However, if you would like to compute and/or use your own values, keep reading.\n",
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"[TODO: LO HAGO O NO LO HAGO?? ###]"
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]
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},
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{
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"attachments": {},
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"First step is get to the effective irradiance. For simplicity, we will copy the procedure explained in the tutorial ``tmy_to_power.ipynb`` [TODO: HOW CAN I LINK THIS?]. Please refer to it to get a more in depth explanation."
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"First step is get to the effective irradiance. For simplicity, we will copy the procedure explained in the tutorial ``tmy_to_power.ipynb``. Please refer to it to get a more in depth explanation."
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]
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},
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{
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"cell_type": "code",
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"execution_count": 2,
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"execution_count": null,
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"metadata": {},
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"outputs": [],
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"source": [
@@ -101,8 +103,9 @@
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"thermal_params = pvlib.temperature.TEMPERATURE_MODEL_PARAMETERS['sapm']['open_rack_glass_polymer']\n",
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"pvtemps = pvlib.temperature.sapm_cell(poa_irrad['poa_global'], tmy_data['temp_air'], tmy_data['wind_speed'], **thermal_params)\n",
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"\n",
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"sandia_modules = pvlib.pvsystem.retrieve_sam(name='SandiaMod')\n",
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"sandia_module = sandia_modules['Canadian_Solar_CS5P_220M___2009_']"
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"# Note that we use the CEC Module provided for the singledionde subsection\n",
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"cec_modules = pvlib.pvsystem.retrieve_sam(name='CECMod')\n",
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"cec_module = cec_modules['Canadian_Solar_Inc__CS5P_220M']"
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]
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},
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{
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},
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{
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"cell_type": "code",
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"execution_count": 9,
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"metadata": {},
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"outputs": [
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{
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"Module type is: c-Si\n"
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]
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}
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],
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"execution_count": null,
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"metadata": {},
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"outputs": [],
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"source": [
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"# First, let's find the airmass and the clearness index\n",
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"# Little caution: default values for this model were fitted obtaining the airmass through the kasten1966 method, not used by default\n",
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" solar_zenith=solar_pos['zenith'],\n",
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" extra_radiation=extra_rad)\n",
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"# Check module is m-Si (monocrystalline silicon)\n",
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"print('Module type is: ' + sandia_module['Material']) #-Reports 'c-Si'\n",
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"print('Module type is: ' + cec_module['Technology'])\n",
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"\n",
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"# Get the mismatch modifiers\n",
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"modifiers = pvlib.spectrum.martin_ruiz_spectral_modifier(clearness,\n",
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" airmass['airmass_absolute'],\n",
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" cell_type='monosi')\n"
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" cell_type='monosi')"
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]
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},
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{
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"attachments": {},
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"And then we can find the modified irradiances by means of a simple multiplication."
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]
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},
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"cell_type": "code",
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"execution_count": 16,
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"execution_count": null,
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"metadata": {},
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"outputs": [],
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"source": [
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"poa_irrad_modified = pd.Series(dtype=pd.Float64Dtype)\n",
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"# TODO: find a pythonic way\n",
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"poa_irrad_modified = pd.Series(dtype=pd.Float64Dtype) # Suppress FutureWarning about dtype default\n",
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"poa_irrad_modified['poa_direct'] = poa_irrad['poa_direct'] * modifiers['direct']\n",
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"poa_irrad_modified['poa_sky_diffuse'] = poa_irrad['poa_sky_diffuse'] * modifiers['sky_diffuse']\n",
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"poa_irrad_modified['poa_ground_diffuse'] = poa_irrad['poa_ground_diffuse'] * modifiers['ground_diffuse']"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 15,
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"metadata": {},
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"outputs": [
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{
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"22.054707712730973\n"
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]
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}
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],
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"source": []
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"execution_count": null,
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"metadata": {},
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"outputs": [],
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"source": [
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"# # TODO: find a pythonic way\n",
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"# poa_irrad_modified2 = pd.Series(dtype=pd.Float64Dtype) # Suppress FutureWarning about dtype default\n",
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"# modifiers2 = modifiers.rename(index={\n",
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"# 'direct': 'poa_direct',\n",
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"# 'sky_diffuse': 'poa_sky_diffuse',\n",
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"# 'ground_diffuse': 'poa_ground_diffuse'\n",
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"# })\n",
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"# poa_irrad_modified2 = poa_irrad.multiply(modifiers2)"
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]
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},
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{
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"attachments": {},
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"Now, we compute the global modified irradiance, to be used in the output power calculation."
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {},
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"outputs": [],
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"source": [
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"poa_irrad_modified = pvlib.irradiance.poa_components(aoi,\n",
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" poa_irrad_modified['poa_direct'],\n",
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" poa_irrad_modified['poa_sky_diffuse'],\n",
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" poa_irrad_modified['poa_ground_diffuse'])"
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]
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},
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{
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"attachments": {},
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"Let's plot the raw vs modified global irradiances, and the difference."
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {},
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"outputs": [],
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"source": [
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"poa_irrad_global_diff = poa_irrad['poa_global'] - poa_irrad_modified['poa_global']\n",
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"poa_irrad['poa_global'].plot()\n",
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"poa_irrad_modified['poa_global'].plot()\n",
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"poa_irrad_global_diff.plot()\n",
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"plt.legend(['Original', 'Modified', 'Difference'])\n",
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"plt.ylabel('Irradiance [W/m²]')\n",
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"plt.show()"
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]
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},
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{
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"attachments": {},
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"Finally, we can get the power result. Instead of using\n",
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"``pvlib.pvsystem.sapm_effective_irradiance``, which already applies another\n",
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"experimental model for the response of the solar module, we have to use the\n",
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"diode model.\n",
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"\n",
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"Have a look to subsection ``DC power using single diode`` in notebook\n",
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"``tmy_to_power.ipynb``. This is just the same two times."
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {},
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"outputs": [],
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"source": [
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"module_params = {k: cec_module[k] for k in ['a_ref', 'I_L_ref', 'I_o_ref', 'R_sh_ref', 'R_s', 'alpha_sc']}"
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]
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},
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{
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"attachments": {},
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"Again, we compute one considering the modifier and another one without it."
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {},
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"outputs": [],
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"source": [
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"# With modifier\n",
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"photocurrent, saturation_current, resistance_series, resistance_shunt, nNsVth = \\\n",
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" pvlib.pvsystem.calcparams_desoto(poa_irrad_modified['poa_global'],\n",
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" pvtemps,\n",
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" EgRef=1.121,\n",
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" dEgdT=-0.0002677,\n",
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" **module_params)\n",
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"single_diode_out_modified = pvlib.pvsystem.singlediode(photocurrent, saturation_current,\n",
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" resistance_series, resistance_shunt,\n",
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" nNsVth)\n",
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"# Without modifier\n",
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"photocurrent, saturation_current, resistance_series, resistance_shunt, nNsVth = \\\n",
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" pvlib.pvsystem.calcparams_desoto(poa_irrad['poa_global'],\n",
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" pvtemps,\n",
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" EgRef=1.121,\n",
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" dEgdT=-0.0002677,\n",
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" **module_params)\n",
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"single_diode_out = pvlib.pvsystem.singlediode(photocurrent, saturation_current,\n",
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" resistance_series, resistance_shunt,\n",
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" nNsVth)"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {},
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"outputs": [],
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"source": [
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"# Calculate difference of max power output\n",
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"single_diode_out_max_pwr_diff = (single_diode_out['p_mp']\n",
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" - single_diode_out_modified['p_mp'])\n",
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"# Plot results\n",
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"single_diode_out['p_mp'].plot()\n",
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"single_diode_out_modified['p_mp'].plot()\n",
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"single_diode_out_max_pwr_diff.plot()\n",
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"plt.legend(['Original', 'Modified', 'Difference'])\n",
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"plt.ylabel('DC Power (W)')\n",
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"plt.show()"
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]
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}
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],
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"metadata": {

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