Add VDI profiles based on lpagg

examples/electricity_demand_example.py

@@ -27,7 +27,7 @@
 import demandlib.bdew as bdew
 import demandlib.particular_profiles as profiles
 
-# The following dictionary is create by "workalendar"
+# The following dictionary has been created by "workalendar"
 # pip3 install workalendar
 # >>> from workalendar.europe import Germany
 # >>> cal = Germany()

examples/vdi_profile_example.py

@@ -0,0 +1,103 @@
+# -*- coding: utf-8 -*-
+"""
+Creating power demand profiles using bdew profiles.
+
+Installation requirements
+-------------------------
+This example requires at least version v0.1.4 of the oemof demandlib. Install
+by:
+    pip install 'demandlib>=0.1.4,<0.2'
+Optional:
+    pip install matplotlib
+
+SPDX-FileCopyrightText: Uwe Krien <krien@uni-bremen.de>
+
+SPDX-License-Identifier: MIT
+
+"""
+
+import datetime
+
+from matplotlib import pyplot as plt
+
+from demandlib import vdi
+
+# The following dictionary has been created by "workalendar"
+# pip3 install workalendar
+# from workalendar.europe import Germany
+# cal = Germany()
+# holidays = dict(cal.holidays(2017))
+
+holidays = {
+    datetime.date(2017, 1, 1): "New year",
+    datetime.date(2017, 4, 14): "Good Friday",
+    datetime.date(2017, 4, 17): "Easter Monday",
+    datetime.date(2017, 5, 1): "Labour Day",
+    datetime.date(2017, 5, 25): "Ascension Thursday",
+    datetime.date(2017, 6, 5): "Whit Monday",
+    datetime.date(2017, 10, 3): "Day of German Unity",
+    datetime.date(2017, 10, 31): "Reformation Day",
+    datetime.date(2017, 12, 25): "Christmas Day",
+    datetime.date(2017, 12, 26): "Second Christmas Day",
+}
+
+
+my_houses = []
+for n in range(2):
+    my_houses.append(
+        {
+            "N_Pers": 3,
+            "name": "EFH_{0}".format(n),
+            "N_WE": 1,
+            "Q_Heiz_a": 6000,
+            "copies": 24,
+            "house_type": "EFH",
+            "Q_TWW_a": 1500,
+            "W_a": 5250,
+            "summer_temperature_limit": 15,
+            "winter_temperature_limit": 5,
+        }
+    )
+    my_houses.append(
+        {
+            "N_Pers": 45,
+            "name": "MFH_{0}".format(n),
+            "N_WE": 15,
+            "Q_Heiz_a": 60000,
+            "copies": 24,
+            "house_type": "MFH",
+            "Q_TWW_a": 15000,
+            "W_a": 45000,
+            "summer_temperature_limit": 15,
+            "winter_temperature_limit": 5,
+        }
+    )
+
+start = datetime.datetime.now()
+
+# To get the DWD TRY region from coordinates the geopandas package is needed.
+# pip3 install geopandas
+# try_region = vdi.find_try_region(13.42, 52.82)
+try_region = 4
+
+# define the region
+my_region = vdi.Region(
+    2017,
+    holidays=holidays,
+    try_region=try_region,
+    houses=my_houses,
+    resample_rule="15min",
+)
+
+# calculate load profiles
+lc = my_region.get_load_curve_houses()
+
+print(datetime.datetime.now() - start)
+lc = lc.groupby(level=[1, 2], axis=1).sum()
+lc = lc.rolling(15).mean()
+print(datetime.datetime.now() - start)
+print(lc)
+
+lc.plot()
+print(lc.sum())
+plt.show()

setup.py

@@ -32,6 +32,7 @@ def read(*names, **kwargs):
             "", read("README.rst")
         )
     ),
+    long_description_content_type="text/x-rst",
     author="oemof developer group",
     author_email="contact@oemof.org",
     url="https://github.com/oemof/demandlib",
@@ -75,5 +76,7 @@ def read(*names, **kwargs):
     },
     extras_require={
         "dev": ["pytest", "sphinx", "sphinx_rtd_theme", "matplotlib"],
+        "examples": ["matplotlib", "workalendar"],
+        "geometry": ["shapely", "geopandas"],
     },
 )

src/demandlib/bdew/elec_slp.py

@@ -180,9 +180,9 @@ def create_dynamic_h0_profile(self):
 
         # Calculate the smoothing factor of the BDEW dynamic H0 profile
         smoothing_factor = (
-            -3.916649251 * 10 ** -10 * decimal_day ** 4
-            + 3.2 * 10 ** -7 * decimal_day ** 3
-            - 7.02 * 10 ** -5 * decimal_day ** 2
+            -3.916649251 * 10**-10 * decimal_day**4
+            + 3.2 * 10**-7 * decimal_day**3
+            - 7.02 * 10**-5 * decimal_day**2
             + 0.0021 * decimal_day
             + 1.24
         )

src/demandlib/bdew/heat_building.py

@@ -241,7 +241,7 @@ def get_sf_values(self, filename="shlp_hour_factors.csv"):
             + (["weekday"] if not residential else [])
         )
 
-        sf_mat = sf_mat.drop(drop_cols, 1)
+        sf_mat = sf_mat.drop(labels=drop_cols, axis=1)
 
         # Determine the h values
         length = len(self.temperature)

src/demandlib/config.py

@@ -0,0 +1,79 @@
+# -*- coding: utf-8 -*-
+
+"""
+Adaptable config reader.
+
+By default the config file of the package is used. Each value can be
+overwritten with a user value with a custom config file in the $HOME directory
+or in the working directory. The name of the config file must be:
+demandlib.ini. If there is such a file in both locations the file in the
+working directory will overwrite the one in the home folder.
+
+SPDX-FileCopyrightText: Steffen - https://github.com/steffenGit
+SPDX-FileCopyrightText: 2016-2021 Uwe Krien <krien@uni-bremen.de>
+
+SPDX-License-Identifier: MIT
+"""
+
+__all__ = [
+    "get",
+    "init",
+]
+
+
+import configparser as cp
+import os
+
+BLACKLIST = ["tox.ini"]
+
+cfg = cp.RawConfigParser()
+cfg.optionxform = str
+_loaded = False
+
+
+def get_ini_filenames():
+    """Returns a list of ini files to use."""
+    paths = []
+    files = []
+
+    paths.append(os.path.join(os.path.dirname(__file__)))
+    paths.append(os.path.join(os.path.expanduser("~")))
+    paths.append(os.getcwd())
+
+    for p in paths:
+        if p == "":  # Empty path string must be ignored
+            continue
+        for f in os.listdir(p):
+            if f == "demandlib.ini":
+                files.append(os.path.join(p, f))
+    return files
+
+
+def init():
+    """Read config file(s)."""
+    cfg.read(get_ini_filenames(), encoding="utf-8")
+    global _loaded
+    _loaded = True
+
+
+def load():
+    if not _loaded:
+        init()
+
+
+def get(section, key):
+    """Returns the value of a given key in a given section."""
+    load()
+    try:
+        return cfg.getint(section, key)
+    except ValueError:
+        try:
+            return cfg.getfloat(section, key)
+        except ValueError:
+            try:
+                return cfg.getboolean(section, key)
+            except ValueError:
+                value = cfg.get(section, key)
+                if value == "None":
+                    value = None
+                return value

src/demandlib/vdi/__init__.py

@@ -0,0 +1,3 @@
+from .dwd_try import find_try_region  # noqa: F401
+from .dwd_try import read_dwd_weather_file  # noqa: F401
+from .regions import Region  # noqa: F401

src/demandlib/vdi/dwd_try.py

@@ -0,0 +1,95 @@
+# -*- coding: utf-8 -*-
+"""
+Read DWD TRY (test reference year) data.
+
+SPDX-FileCopyrightText: Joris Zimmermann
+SPDX-FileCopyrightText: Uwe Krien
+
+SPDX-License-Identifier: MIT
+"""
+
+import os
+
+import pandas as pd
+
+try:
+    import geopandas as gpd
+    from shapely.geometry import Point
+except ModuleNotFoundError:
+    pass
+
+
+def find_try_region(longitude, latitude):
+    """
+    Find the DWD TRY region by coordinates.
+
+    Notes
+    -----
+    The packages geopandas and shapely need to be installed to use this
+    function.
+
+    Parameters
+    ----------
+    longitude : float
+    latitude : float
+
+    Returns
+    -------
+    DWD TRY region. : int
+
+    """
+    fn_try_map = os.path.join(
+        os.path.dirname(__file__), "resources_weather", "TRY_polygons.geojson"
+    )
+    try_map = gpd.read_file(fn_try_map)
+    my_point = Point(longitude, latitude)
+    return int(try_map.loc[try_map.contains(my_point), "TRY_code"])
+
+
+def read_dwd_weather_file(weather_file_path=None, try_region=None):
+    """Read and interpolate 'DWD Testreferenzjahr' files."""
+    if weather_file_path is None:
+        weather_file_path = os.path.join(
+            os.path.dirname(__file__),
+            "resources_weather",
+            "TRY2010_{:02d}_Jahr.dat".format(try_region),
+        )
+    # The comments in DWD files before the header are not commented out.
+    # Thus we have to search for the line with the header information:
+    header_row = None
+    with open(weather_file_path, "r") as rows:
+        for number, row in enumerate(rows, 1):
+            # The header is the row before the appearance of '***'
+            if "***" in row:
+                header_row = number - 1
+                break
+
+    # Plausibility check:
+    if header_row is None:
+        msg = (
+            "Error: Header row not found in weather file. "
+            'Is the data type "DWD" correct? Exiting...\nFile is: '
+            + weather_file_path
+        )
+        raise TypeError(msg)
+
+    # Read the file and store it in a DataFrame
+    weather_data = pd.read_csv(
+        weather_file_path,
+        delim_whitespace=True,
+        skiprows=header_row - 1,
+        index_col=["MM", "DD", "HH"],
+        usecols=["MM", "DD", "HH", "t", "N"],
+        comment="*",
+    )
+
+    # Rename the columns
+    weather_data.rename(
+        columns={
+            "t": "TAMB",
+            "N": "CCOVER",
+        },
+        inplace=True,
+    )
+
+    return weather_data