{ "cells": [ { "cell_type": "markdown", "metadata": {}, "source": [ "# Example for using the WindpowerlibTurbine model\n", "\n", "The `WindpowerlibTurbine` model can be used to determine the feed-in of a wind turbine using the windpowerlib.\n", "The [windpowerlib](https://github.com/wind-python/windpowerlib) is a python library for simulating the performance of wind turbines and farms. For more information about the model check the [documentation of the windpowerlib](https://windpowerlib.readthedocs.io/en/stable/).\n", "\n", "The following example shows you how to use the `WindpowerlibTurbine` model.\n", "\n", "* [Set up WindPowerPlant object](#windpowerplant_object)\n", "* [Get weather data](#weather_data)\n", "* [Calculate feed-in](#feedin)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Set up WindPowerPlant object \n", "\n", "To calculate the feed-in using the `WindpowerlibTurbine` model you have to set up a `WindPowerPlant` object. You can import it as follows:" ] }, { "cell_type": "code", "execution_count": 1, "metadata": {}, "outputs": [], "source": [ "from feedinlib import WindPowerPlant" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "The wind power plant must have all power plant parameters required by the `WindpowerlibTurbine` model. The required parameters can be looked up in the [model's documentation](https://feedinlib.readthedocs.io/en/features-design-skeleton/temp/feedinlib.models.WindpowerlibTurbine.html#feedinlib.models.WindpowerlibTurbine.power_plant_requires).\n", "\n", "The `WindpowerlibTurbine` model requires you to provide the turbine's **hub height** as well as the turbine's **power curve** or **power coefficient curve**. Alternatively to providing the curve(s) directly you can provide the **turbine type** which will retrieve the turbine's power and/or power coefficient curve from a wind turbine library provided along with the windpowerlib. For an overview of the provided wind turbines you can use the function `get_power_plant_data()`." ] }, { "cell_type": "code", "execution_count": 2, "metadata": {}, "outputs": [], "source": [ "from feedinlib import get_power_plant_data" ] }, { "cell_type": "code", "execution_count": 3, "metadata": {}, "outputs": [ { "data": { "text/html": [ "
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manufacturerturbine_typehas_power_curvehas_cp_curve
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" ], "text/plain": [ " manufacturer turbine_type has_power_curve has_cp_curve\n", "1 Enercon E-101/3050 True True\n", "2 Enercon E-101/3500 True True\n", "3 Enercon E-115/3000 True True\n", "4 Enercon E-115/3200 True True" ] }, "execution_count": 3, "metadata": {}, "output_type": "execute_result" } ], "source": [ "# get wind turbines\n", "turbine_df = get_power_plant_data(dataset='oedb_turbine_library')\n", "# print the first four turbines\n", "turbine_df.iloc[1:5, :]" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Now you can set up a wind turbine to calculate feed-in for:" ] }, { "cell_type": "code", "execution_count": 4, "metadata": {}, "outputs": [], "source": [ "# set up wind turbine using the wind turbine library\n", "turbine_data = {\n", " 'turbine_type': 'E-101/3050', # turbine name as in turbine library\n", " 'hub_height': 135 # in m\n", " }\n", "wind_turbine = WindPowerPlant(**turbine_data)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Get weather data \n", "\n", "Besides setting up your wind turbine you have to provide weather data the feed-in is calculated with.\n", "This example uses open_FRED weather data. For more information on the data and download see the [load_open_fred_weather_data Notebook](load_open_fred_weather_data.ipynb)." ] }, { "cell_type": "code", "execution_count": 5, "metadata": {}, "outputs": [], "source": [ "from feedinlib.db import Weather\n", "from feedinlib.db import defaultdb\n", "from shapely.geometry import Point" ] }, { "cell_type": "code", "execution_count": 6, "metadata": {}, "outputs": [], "source": [ "# specify latitude and longitude of wind turbine location\n", "location = Point(13.5, 52.4)" ] }, { "cell_type": "code", "execution_count": 7, "metadata": {}, "outputs": [], "source": [ "# download weather data for June 2017\n", "open_FRED_weather_data = Weather(\n", " start='2017-06-01', stop='2017-07-01', \n", " locations=[location],\n", " heights=[140, 160],\n", " variables=\"windpowerlib\",\n", " **defaultdb())" ] }, { "cell_type": "code", "execution_count": 9, "metadata": {}, "outputs": [ { "ename": "KeyError", "evalue": "('roughness_length', 0.0)", 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"# get weather data in windpowerlib format\n", "weather_df = open_FRED_weather_data.df(location=location, lib=\"windpowerlib\")" ] }, { "cell_type": "code", "execution_count": 10, "metadata": {}, "outputs": [ { "ename": "NameError", "evalue": "name 'weather_df' is not defined", "output_type": "error", "traceback": [ "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m", "\u001b[0;31mNameError\u001b[0m Traceback (most recent call last)", "\u001b[0;32m\u001b[0m in \u001b[0;36m\u001b[0;34m\u001b[0m\n\u001b[1;32m 2\u001b[0m \u001b[0;32mimport\u001b[0m \u001b[0mmatplotlib\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mpyplot\u001b[0m \u001b[0;32mas\u001b[0m \u001b[0mplt\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 3\u001b[0m \u001b[0mget_ipython\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mrun_line_magic\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m'matplotlib'\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m'inline'\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m----> 4\u001b[0;31m \u001b[0mweather_df\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mloc\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m[\u001b[0m\u001b[0;34m'wind_speed'\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mplot\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mtitle\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;34m'Wind speed'\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 5\u001b[0m \u001b[0mplt\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mxlabel\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m'Time'\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 6\u001b[0m \u001b[0mplt\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mylabel\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m'Wind speed in m/s'\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m;\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n", "\u001b[0;31mNameError\u001b[0m: name 'weather_df' is not defined" ] } ], "source": [ "# plot wind speed\n", "import matplotlib.pyplot as plt\n", "%matplotlib inline\n", "weather_df.loc[:, ['wind_speed']].plot(title='Wind speed')\n", "plt.xlabel('Time')\n", "plt.ylabel('Wind speed in m/s');" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Calculate feed-in \n", "\n", "The feed-in can be calculated by calling the `WindPowerPlant`'s `feedin` method with the weather data." ] }, { "cell_type": "code", "execution_count": 12, "metadata": {}, "outputs": [], "source": [ "feedin = wind_turbine.feedin(\n", " weather=weather_df)" ] }, { "cell_type": "code", "execution_count": 13, "metadata": { "scrolled": true }, "outputs": [ { "data": { "image/png": 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\n", "text/plain": [ "
" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "# plot calculated feed-in\n", "import matplotlib.pyplot as plt\n", "%matplotlib inline\n", "feedin.plot(title='Wind turbine feed-in')\n", "plt.xlabel('Time')\n", "plt.ylabel('Power in W');" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "**Scaled feed-in**\n", "\n", "The wind turbine feed-in can also be automatically scaled by the turbine's nominal power." ] }, { "cell_type": "code", "execution_count": 14, "metadata": {}, "outputs": [], "source": [ "# calculate scaled feed-in\n", "feedin_scaled = wind_turbine.feedin(\n", " weather=weather_df,\n", " scaling='nominal_power')" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "The turbine's nominal power can be retrieved as follows:" ] }, { "cell_type": "code", "execution_count": 15, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "3050000.0" ] }, "execution_count": 15, "metadata": {}, "output_type": "execute_result" } ], "source": [ "wind_turbine.nominal_power" ] }, { "cell_type": "code", "execution_count": 16, "metadata": {}, "outputs": [ { "data": { "image/png": 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\n", 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" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "# plot calculated feed-in\n", "import matplotlib.pyplot as plt\n", "%matplotlib inline\n", "feedin_scaled.plot(title='Scaled wind turbine feed-in')\n", "plt.xlabel('Time')\n", "plt.ylabel('Power in W');" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "**Feed-in with optional model parameters**\n", "\n", "In order to change the default calculation configurations of the `WindpowerlibTurbine` model to e.g. use the turbine's power coefficient curve instead of power curve you can pass further parameters to the `feedin` method. An overview of which further parameters may be provided is documented under the [feedin method](https://feedinlib.readthedocs.io/en/features-design-skeleton/temp/feedinlib.models.WindpowerlibTurbine.html#feedinlib.models.WindpowerlibTurbine.feedin)'s kwargs." ] }, { "cell_type": "code", "execution_count": 17, "metadata": {}, "outputs": [], "source": [ "# use density corrected power curve to calculate feed-in\n", "feedin_density_corrected = wind_turbine.feedin(\n", " weather=weather_df,\n", " density_correction=True)" ] }, { "cell_type": "code", "execution_count": 18, "metadata": {}, "outputs": [ { "data": { "image/png": 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\n", 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" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "# plot calculated feed-in\n", "import matplotlib.pyplot as plt\n", "%matplotlib inline\n", "feedin_density_corrected.plot(title='Wind turbine feed-in', legend=True,\n", " label='density corrected power curve')\n", "feedin.plot(legend=True, label='power curve')\n", "plt.xlabel('Time')\n", "plt.ylabel('Power in W');" ] }, { "cell_type": "code", "execution_count": 19, "metadata": {}, "outputs": [], "source": [ "# use power coefficient curve to calculate feed-in\n", "feedin_coefficient_curve = wind_turbine.feedin(\n", " weather=weather_df,\n", " power_output_model='power_coefficient_curve')" ] }, { "cell_type": "code", "execution_count": 20, "metadata": {}, "outputs": [ { "data": { "image/png": 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\n", 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" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "# plot calculated feed-in\n", "import matplotlib.pyplot as plt\n", "%matplotlib inline\n", "feedin_coefficient_curve.plot(title='Wind turbine feed-in', legend=True,\n", " label='power coefficient curve')\n", "feedin.plot(legend=True, label='power curve')\n", "plt.xlabel('Time')\n", "plt.ylabel('Power in W');" ] } ], "metadata": { "kernelspec": { "display_name": "Python 3", "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": "3.6.7" } }, "nbformat": 4, "nbformat_minor": 2 }