{ "cells": [ { "cell_type": "markdown", "metadata": {}, "source": [ "\n", "\n", "\n", "# Tutorial 3 - Module Temperature\n", "\n", "This notebook shows how to use pvlib to estimate PV cell temperature, a secondary driver that affects the PV conversion efficiency.\n", "\n", "\n", "\n" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## PV Concepts in this lesson:\n", "\n", "* cell and module temperature\n", "* NSRDB data\n", "* TMY files\n", "\n", "## Python concepts in this lesson:\n", "\n", "* file system paths in Python with [`pathlib`](https://docs.python.org/3/library/pathlib.html)\n", "* parsing NSRDB data with [`pvlib.iotools.read_tmy3`](https://pvlib-python.readthedocs.io/en/stable/reference/generated/pvlib.iotools.read_tmy3.html)\n", "* dates, times, and timedeltas in Python\n", "* solar position with [`pvlib.solarposition.get_solarposition`](https://pvlib-python.readthedocs.io/en/stable/reference/generated/pvlib.solarposition.get_solarposition.html)\n", "* single-axis tracking in [`pvlib.tracking.singleaxis`](https://pvlib-python.readthedocs.io/en/stable/reference/generated/pvlib.tracking.singleaxis.html) -- check out this [singleaxis tracking example](https://pvlib-python.readthedocs.io/en/stable/gallery/solar-tracking/plot_single_axis_tracking.html) in the gallery\n", "* Calculate module cell temperature with [Sandia Array Performance Model (SAPM)](https://pvlib-python.readthedocs.io/en/stable/reference/generated/pvlib.temperature.sapm_cell.html)\n", "* making [matplotlib scatterplots](https://matplotlib.org/stable/api/_as_gen/matplotlib.pyplot.scatter.html) with a [colorbar](https://matplotlib.org/stable/api/_as_gen/matplotlib.pyplot.colorbar.html)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## What affects module temperature?\n", "\n", "If PV modules were 100% efficient, they would convert 100% of collected irradiance into electrical energy. However, today's PV modules are on the order of 20% efficient, meaning that after accounting for reflection, soiling, spectral mismatch, and the glass, the other 80% of sunlight collected is converted to thermal energy. This thermal energy causes the temperature of the module to rise above ambient conditions, eventually reaching a steady state defined by a heat balance of power in (solar irradiance) vs power out (thermal radiation, convective cooling, etc). With that in mind, the primary drivers of module temperature are POA irradiance, ambient temperature, and wind speed. \n", "\n", "A distinction that is often ignored is the difference between module temperature and cell temperature. In theory, the temperature of the P-N junction inside the cell is what affects conversion efficiency, but this is difficult to measure. In practice, the temperature of the module backsheet is often a usable approximation, though it is often 1-2 degrees Celsius cooler than the junction temperature.\n", "\n", "## Modeling module temperature\n", "\n", "Some PV thermal models go to the trouble of modeling the entire heat balance equation, but much simpler models are available and are often accurate enough. Here we will use the thermal model from the Sandia Array Performance Model (SAPM) to estimate cell temperature from ambient conditions. The SAPM thermal model takes only POA irradiance, ambient temperature, and wind speed as weather inputs, but it also requires a set of parameters that characterize the thermal properties of the module of interest. More on that later.\n", "\n", "First, let's use the procedure of previous tutorials to get the relevant inputs for a tracking array:" ] }, { "cell_type": "code", "execution_count": 1, "metadata": {}, "outputs": [], "source": [ "# if running on google colab, uncomment the next line and execute this cell to install the dependencies and prevent \"ModuleNotFoundError\" in later cells:\n", "# !pip install -r https://raw.githubusercontent.com/PVSC-Python-Tutorials/PVSC50/main/requirements.txt" ] }, { "cell_type": "code", "execution_count": 2, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "0.9.4.dev19+ge4356f9\n" ] } ], "source": [ "import pvlib\n", "import pandas as pd # for data wrangling\n", "import matplotlib.pyplot as plt # for visualization\n", "import pathlib # for finding the example dataset\n", "\n", "print(pvlib.__version__)" ] }, { "cell_type": "code", "execution_count": 3, "metadata": {}, "outputs": [], "source": [ "# create a path to the pvlib \"data\" folder using Python pathlib,\n", "# note how you can use `.__file__` to get the path to the pvlib module,\n", "# the `.parent` attribute to get the directory containing a file,\n", "# and \"/\" operator add nested folders to the path. Then read a TMY3 file\n", "# that comes with pvlib python in the \"data\" folder, coercing the year to 1990\n", "DATA_DIR = pathlib.Path(pvlib.__file__).parent / 'data'\n", "df_tmy, metadata = pvlib.iotools.read_tmy3(DATA_DIR / '723170TYA.CSV', coerce_year=1990)\n", "\n", "# pvlib iotools.read_tmy3 returns a Pandas DataFrame of the timeseries\n", "# and dictionary of metadata. Use the coordinates of the TMY3 file to\n", "# create a pvlib python \"location\"\n", "location = pvlib.location.Location(\n", " latitude=metadata['latitude'], longitude=metadata['longitude'])\n", "\n", "# offset the hourly timeseries by 30-minutes to get the solar positions at the\n", "# center of each interval\n", "times = df_tmy.index - pd.Timedelta('30min')\n", "solar_position = location.get_solarposition(times)\n", "# shift the times to the right side of each interval\n", "solar_position.index += pd.Timedelta('30min')\n", "\n", "# calculate the positions at each timestep for a north-south aligned tracker\n", "# note by default backtrack is true and GCR = 1/7\n", "tracker_data = pvlib.tracking.singleaxis(\n", " solar_position['apparent_zenith'], solar_position['azimuth'], axis_azimuth=180)\n", "# set nighttime tracker positions to stow (zero-degrees is horizontal)\n", "tilt = tracker_data['surface_tilt'].fillna(0)\n", "azimuth = tracker_data['surface_azimuth'].fillna(0)\n", "\n", "# get the irradiance components in the plane of the array at each timestep\n", "df_poa_tracker = pvlib.irradiance.get_total_irradiance(\n", " surface_tilt=tilt,\n", " surface_azimuth=azimuth,\n", " dni=df_tmy['DNI'],\n", " ghi=df_tmy['GHI'],\n", " dhi=df_tmy['DHI'],\n", " solar_zenith=solar_position['apparent_zenith'],\n", " solar_azimuth=solar_position['azimuth'])\n", "tracker_poa = df_poa_tracker['poa_global']" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Now that we have the necessary weather inputs, all that is left are the thermal parameters. These characterize the thermal properties of the module as well as the module's mounting configuration. Parameter values covering the common system designs are provided with pvlib:" ] }, { "cell_type": "code", "execution_count": 4, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "['open_rack_glass_glass',\n", " 'close_mount_glass_glass',\n", " 'open_rack_glass_polymer',\n", " 'insulated_back_glass_polymer']" ] }, "execution_count": 4, "metadata": {}, "output_type": "execute_result" } ], "source": [ "all_parameters = pvlib.temperature.TEMPERATURE_MODEL_PARAMETERS['sapm']\n", "list(all_parameters.keys())" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "`open_rack_glass_polymer` is appropriate for many large-scale systems (polymer backsheet; open racking), so we will use it here:" ] }, { "cell_type": "code", "execution_count": 5, "metadata": {}, "outputs": [], "source": [ "parameters = all_parameters['open_rack_glass_polymer']\n", "# note the \"splat\" operator \"**\" which expands the dictionary \"parameters\"\n", "# into a comma separated list of keyword arguments\n", "cell_temperature = pvlib.temperature.sapm_cell(\n", " tracker_poa, df_tmy['DryBulb'], df_tmy['Wspd'], **parameters)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Now let's compare ambient temperature with cell temperature. Notice how our modeled cell temperature rises significantly above ambient temperature during the day, especially on sunny days:" ] }, { "cell_type": "code", "execution_count": 6, "metadata": {}, "outputs": [ { "data": { "image/png": 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\n", "text/plain": [ "<Figure size 640x480 with 1 Axes>" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "df_tmy['DryBulb'].head(24*7).plot()\n", "cell_temperature.head(24*7).plot()\n", "plt.grid()\n", "plt.legend(['Dry Bulb', 'Cell Temperature'])\n", "# note Python 3 can use unicode characters like the degrees symbol\n", "plt.ylabel('Temperature [°C]');" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Wind speed also has an effect, but it's harder to see in a time series plot like this. To make it clearer, let's make a scatter plot: " ] }, { "cell_type": "code", "execution_count": 7, "metadata": {}, "outputs": [ { "data": { "image/png": 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\n", "text/plain": [ "<Figure size 640x480 with 2 Axes>" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "temperature_difference = cell_temperature - df_tmy['DryBulb']\n", "plt.scatter(tracker_poa, temperature_difference, c=df_tmy['Wspd'])\n", "plt.colorbar()\n", "# note you can use LaTeX math in matplotlib labels\n", "# compare \\degree\" with the unicode symbol above\n", "plt.ylabel('Temperature rise above ambient [$\\degree C$]')\n", "plt.xlabel('POA Irradiance [$W/m^2$]');\n", "plt.title('Cell temperature rise, colored by wind speed');" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "The main trend is a bigger temperature difference as incident irradiance increases. However, this plot shows that higher wind speed reduces the effect -- faster wind means more convective cooling, so a lower cell temperature than it would be in calm air.\n", "\n", "Note: the gap at the upper edge of the trend is an artifact of the low resolution of wind speed values in this TMY dataset; there are no values between 0 and 0.3 m/s." ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Pop Quiz\n", "Now it's your turn. There's another, older TMY3 file in the pvlib data folder: \"703165TY.csv\".\n", "1. Create a path to the TMY3 file: \"703165TY.csv\" using `DATA_DIR` and the `/` operator\n", "2. read the timeseries and metadata from the file\n", "3. What is the name of the station in the metadata?\n", "4. Assuming a glass polymer module on a horizontally flat rooftop, use the SAPM to calculate the cell temperature\n", " - What is the plane of array irradiance incident on the horizontal rooftop module?\n", " - What parameters should be used for a rooftop module?\n", "5. In the same plot compare the first week of ambient temperature data with the calculated cell temperatures" ] }, { "cell_type": "code", "execution_count": 8, "metadata": {}, "outputs": [], "source": [ "mypath = DATA_DIR / 'path to TMY3 file goes here'\n", "# now use pvlib.iotools.read_tmy3 to get the data, what station is it?\n" ] }, { "cell_type": "code", "execution_count": 9, "metadata": {}, "outputs": [], "source": [ "# make a plot of the 1st week ambient & calculated cell temperatures\n" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "[](http://creativecommons.org/licenses/by/4.0/)\n", "\n", "This work is licensed under a [Creative Commons Attribution 4.0 International License](http://creativecommons.org/licenses/by/4.0/)." ] } ], "metadata": { "kernelspec": { "display_name": "Python 3 (ipykernel)", "language": "python", "name": "python3" }, "language_info": { "codemirror_mode": { "name": "ipython", "version": 3 }, "file_extension": ".py", "mimetype": "text/x-python", "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", "version": "3.9.13" } }, "nbformat": 4, "nbformat_minor": 4 }