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| """ | ||
| The ``turbine_cluster_modelchain_example`` module shows how to calculate the | ||
| power output of wind farms and wind turbine clusters with the windpowerlib. | ||
| A cluster can be useful if you want to calculate the feed-in of a region for | ||
| which you want to use one single weather data point. | ||
| Functions that are used in the ``modelchain_example``, like the initialization | ||
| of wind turbines, are imported and used without further explanations. | ||
| SPDX-FileCopyrightText: 2019 oemof developer group <[email protected]> | ||
| SPDX-License-Identifier: MIT | ||
| """ | ||
| import pandas as pd | ||
| import requests | ||
| import os | ||
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| from windpowerlib import WindFarm | ||
| from windpowerlib import WindTurbine | ||
| from windpowerlib import TurbineClusterModelChain | ||
| from windpowerlib import WindTurbineCluster | ||
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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 | ||
| import logging | ||
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| logging.getLogger().setLevel(logging.INFO) | ||
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| def get_weather_data(filename="weather.csv", **kwargs): | ||
| r""" | ||
| Imports weather data from a file. | ||
| 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. The height in m for which the data applies is | ||
| specified in the second row. | ||
| In case no weather data file exists, an example weather data file is | ||
| automatically downloaded and stored in the same directory as this example. | ||
| Parameters | ||
| ---------- | ||
| filename : str | ||
| Filename of the weather data file. Default: 'weather.csv'. | ||
| Other Parameters | ||
| ---------------- | ||
| datapath : str, optional | ||
| Path where the weather data file is stored. | ||
| Default is the same directory this example is stored in. | ||
| Returns | ||
| ------- | ||
| :pandas:`pandas.DataFrame<frame>` | ||
| DataFrame with time series for wind speed `wind_speed` in m/s, | ||
| temperature `temperature` in K, roughness length `roughness_length` | ||
| in m, and pressure `pressure` in Pa. | ||
| The columns of the DataFrame are a MultiIndex where the first level | ||
| contains the variable name as string (e.g. 'wind_speed') and the | ||
| second level contains the height as integer at which it applies | ||
| (e.g. 10, if it was measured at a height of 10 m). The index is a | ||
| DateTimeIndex. | ||
| """ | ||
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| if "datapath" not in kwargs: | ||
| kwargs["datapath"] = os.path.dirname(__file__) | ||
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| file = os.path.join(kwargs["datapath"], filename) | ||
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| # download example weather data file in case it does not yet exist | ||
| if not os.path.isfile(file): | ||
| logging.debug("Download weather data for example.") | ||
| req = requests.get("https://osf.io/59bqn/download") | ||
| with open(file, "wb") as fout: | ||
| fout.write(req.content) | ||
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| # read csv file | ||
| weather_df = pd.read_csv( | ||
| file, | ||
| index_col=0, | ||
| header=[0, 1], | ||
| date_parser=lambda idx: pd.to_datetime(idx, utc=True), | ||
| ) | ||
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| # change time zone | ||
| weather_df.index = weather_df.index.tz_convert("Europe/Berlin") | ||
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| return weather_df | ||
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| def run_example(): | ||
| r""" | ||
| Runs the example. | ||
| """ | ||
| weather = get_weather_data("weather.csv") | ||
| e126 = WindTurbine( | ||
| **{ | ||
| "turbine_type": "E-126/4200", # turbine type as in register | ||
| "hub_height": 135, # in m | ||
| } | ||
| ) | ||
| v90 = WindTurbine( | ||
| **{ | ||
| "turbine_type": "V90/2000", # turbine name as in register | ||
| "hub_height": 120, # in m | ||
| } | ||
| ) | ||
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| # specification of wind farm data (2) containing a wind farm efficiency | ||
| # wind turbine fleet is provided using the to_group function | ||
| example_farm = WindFarm( | ||
| **{ | ||
| "name": "example_farm_2", | ||
| "wind_turbine_fleet": [ | ||
| v90.to_group(number_turbines=6), | ||
| e126.to_group(total_capacity=12.6e6), | ||
| ], | ||
| "efficiency": 0.5 | ||
| } | ||
| ) | ||
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| example_cluster = WindTurbineCluster(**{ | ||
| "name": "Offshore_cluster", | ||
| "wind_farms": [example_farm, example_farm], | ||
| }) | ||
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| # ModelChain with wind farm | ||
| mc_farm = TurbineClusterModelChain( | ||
| example_farm, wake_losses_model=None, | ||
| ).run_model(weather) | ||
| flh_farm = mc_farm.power_output.sum() / example_farm.nominal_power | ||
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| # ModelChain with wind cluster | ||
| mc_cluster = TurbineClusterModelChain( | ||
| example_cluster, wake_losses_model=None, | ||
| ).run_model(weather) | ||
| flh_cluster = mc_cluster.power_output.sum() / example_cluster.nominal_power | ||
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| print("Full Load Hours of cluster:", flh_cluster) | ||
| print("Full Load Hours of farm:", flh_farm) | ||
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| if __name__ == "__main__": | ||
| run_example() |
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