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Birgit SchachlerBirgit Schachler
Birgit Schachler
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Birgit Schachler
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Add jupyter notebook with basic example
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‎example/basic_example.ipynb‎

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{
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"cells": [
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"This example shows you the basic usage of the windpowerlib. There are mainly three steps.\n",
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"First you need to define your wind turbine, then get your weather data and in the last step call the windpowerlib ModelChain to generate your feedin timeseries.\n",
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"Be careful with the units!"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"### Import necessary packages and modules"
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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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"collapsed": true
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},
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"outputs": [],
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"source": [
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"__copyright__ = \"Copyright oemof developer group\"\n",
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"__license__ = \"GPLv3\"\n",
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"\n",
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"import os\n",
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"import pandas as pd\n",
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"\n",
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"from windpowerlib import modelchain\n",
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"from windpowerlib import wind_turbine as wt"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"You can use the logging package to get logging messages from the windpowerlib. Change the logging level if you want more or less messages."
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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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"collapsed": true
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},
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"outputs": [],
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"source": [
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"import logging\n",
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"logging.getLogger().setLevel(logging.DEBUG)"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"### Import weather data\n",
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"\n",
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"The function below imports the example weather data from the weather.csv file provided along with the windpowerlib. The data include wind speed at two different heights in m/s, air temperature in two different heights in K, surface roughness length in m and air pressure in Pa.\n",
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"\n",
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"To find out which weather data in which units need to be provided in order to use the ModelChain or other functions of the windpowerlib see the individual function documentation."
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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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"collapsed": true
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},
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"outputs": [],
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"source": [
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"def read_weather_data(filename, datetime_column='Unnamed: 0',\n",
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" **kwargs):\n",
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" r\"\"\"\n",
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" Fetches weather data from a file.\n",
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"\n",
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" The files are located in the example folder of the windpowerlib.\n",
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"\n",
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" Parameters\n",
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" ----------\n",
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" filename : string\n",
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" Filename of the weather data file.\n",
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" datetime_column : string\n",
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" Name of the datetime column of the weather DataFrame.\n",
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"\n",
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" Other Parameters\n",
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" ----------------\n",
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" datapath : string, optional\n",
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" Path where the weather data file is stored.\n",
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" Default: 'windpowerlib/example'.\n",
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"\n",
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" Returns\n",
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" -------\n",
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" pandas.DataFrame\n",
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" Contains weather data time series.\n",
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"\n",
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" \"\"\"\n",
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" if 'datapath' not in kwargs:\n",
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" kwargs['datapath'] = os.path.join(os.path.split(\n",
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" os.path.dirname(__file__))[0], 'example')\n",
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"\n",
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" file = os.path.join(kwargs['datapath'], filename)\n",
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" df = pd.read_csv(file)\n",
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" return df.set_index(pd.to_datetime(df[datetime_column])).tz_localize(\n",
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" 'UTC').tz_convert('Europe/Berlin').drop(datetime_column, 1)\n",
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"\n",
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"\n",
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"# Read weather data from csv\n",
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"weather = read_weather_data('weather.csv')"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"Along with the weather data you have to provide a dataframe or dictionary specifying the height for which the data applies."
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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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"collapsed": true
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},
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"outputs": [],
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"source": [
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"data_height = {\n",
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" 'pressure': 0,\n",
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" 'temp_air': 2,\n",
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" 'v_wind': 10,\n",
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" 'temp_air_2': 10,\n",
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" 'v_wind_2': 80}"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"### Initialise wind turbine"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"There are two ways to initialize a WindTurbine object. You can either specify your own turbine, as done below or use"
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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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"collapsed": true
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},
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"outputs": [],
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"source": [
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"wt.get_turbine_types()\n",
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"turbines[turbines[\"turbine_id\"].str.contains(\"VESTAS\")]"
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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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"collapsed": true
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},
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"outputs": [],
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"source": [
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"# Specifications of the wind turbines\n",
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"enerconE126 = {\n",
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" 'hub_height': 135,\n",
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" 'd_rotor': 127,\n",
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" 'fetch_curve': 'P', # 'P' vor p-curve and 'cp' for cp-curve\n",
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" 'turbine_name': 'ENERCON E 126 7500'} # Turbine name as in register. Use\n",
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" # wind_turbine.get_turbine_types()\n",
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"P_data = {0:\n",
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" 3:\n",
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" 5:\n",
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" 10:\n",
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" 15:\n",
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" 20:\n",
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" 25:}\n",
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"# for a full list.\n",
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"vestasV90 = {\n",
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" 'hub_height': 105,\n",
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" 'd_rotor': 90,\n",
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" 'fetch_curve': 'P',\n",
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" 'turbine_name': 'VESTAS V 90 3000'}\n",
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"\n",
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"# Initialize WindTurbine objects\n",
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"e126 = wt.WindTurbine(**enerconE126)\n",
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"v90 = wt.WindTurbine(**vestasV90)"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"### Use the ModelChain to generate feedin timeseries"
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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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"collapsed": true
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},
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"outputs": [],
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"source": [
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"# Specifications of the modelchain data\n",
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"modelchain_data = {\n",
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" 'obstacle_height': 0,\n",
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" 'wind_model': 'logarithmic', # 'logarithmic' or 'hellman'\n",
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" 'rho_model': 'ideal_gas', # 'barometric' or 'ideal_gas'\n",
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" 'power_output_model': 'p_values', # 'p_values' or 'cp_values'\n",
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" 'density_corr': False, # True or False\n",
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" 'hellman_exp': None} # Float or None\n",
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"\n",
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"# Calculate turbine power output\n",
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"mc_e126 = modelchain.ModelChain(e126, **modelchain_data).run_model(\n",
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" weather, coastDat2)\n",
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"e126.power_output = mc_e126.power_output\n",
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"mc_v90 = modelchain.ModelChain(v90, **modelchain_data).run_model(\n",
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" weather, coastDat2)\n",
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"v90.power_output = mc_v90.power_output\n",
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"\n",
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"\n"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"### Plot results"
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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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"collapsed": true
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},
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"outputs": [],
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"source": [
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"try:\n",
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" from matplotlib import pyplot as plt\n",
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"except ImportError:\n",
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" plt = None\n",
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"# Plot turbine power output\n",
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"if plt:\n",
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" e126.power_output.plot(legend=True, label='Enercon E126')\n",
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" v90.power_output.plot(legend=True, label='Vestas V90')\n",
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" plt.show()\n",
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"else:\n",
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" print(e126.power_output)\n",
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" print(v90.power_output)\n",
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"\n",
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"# Plot power (coefficient) curves\n",
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"if plt:\n",
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" if e126.cp_values is not None:\n",
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" e126.cp_values.plot(style='*', title='Enercon E126')\n",
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" plt.show()\n",
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" if e126.p_values is not None:\n",
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" e126.p_values.plot(style='*', title='Enercon E126')\n",
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" plt.show()\n",
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" if v90.cp_values is not None:\n",
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" v90.cp_values.plot(style='*', title='Vestas V90')\n",
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" plt.show()\n",
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" if v90.p_values is not None:\n",
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" v90.p_values.plot(style='*', title='Vestas V90')\n",
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" plt.show()\n",
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"else:\n",
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" if e126.cp_values is not None:\n",
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" print(\"The cp value at a wind speed of 5 m/s: {0}\".format(\n",
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" e126.cp_values.cp[5.0]))\n",
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" if e126.p_values is not None:\n",
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" print(\"The P value at a wind speed of 5 m/s: {0}\".format(\n",
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" e126.p_values.P[5.0]))\n",
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"logging.info('Done!')"
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]
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}
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],
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"metadata": {
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"kernelspec": {
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"display_name": "Python 3",
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"language": "python",
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"name": "python3"
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},
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"language_info": {
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"codemirror_mode": {
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"name": "ipython",
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"version": 3
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},
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"file_extension": ".py",
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"mimetype": "text/x-python",
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"name": "python",
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"nbconvert_exporter": "python",
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"pygments_lexer": "ipython3",
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"version": "3.4.2"
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}
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},
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"nbformat": 4,
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"nbformat_minor": 2
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}

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