Merge pull request #79 from oemof/dev

Release v0.2.2

Author: p-snft

.github/workflows/tox_pytests.yml

@@ -16,7 +16,7 @@ jobs:
     runs-on: ubuntu-latest
     strategy:
       matrix:
-        python-version: ["3.9", "3.10", "3.11"]
+        python-version: ["3.10", "3.11", "3.12"]
 
     steps:
     - uses: actions/checkout@v4

.readthedocs.yml

@@ -3,7 +3,7 @@ version: 2
 build:
   os: ubuntu-22.04
   tools:
-    python: "3.8"
+    python: "3.10"
 sphinx:
   configuration: docs/conf.py
 formats: all

CHANGELOG.rst

@@ -1,6 +1,20 @@
 Changelog
 =========
 
+v0.2.2 (YYYY-MM-DD)
++++++++++++++++++++++++++
+
+New features
+############
+*   Added Electricity standard load profiles as released by the BDEW in 2025.
+
+Bug fixes
+#########
+
+Other changes
+#############
+
+
 v0.2.1 (2024-08-06)
 +++++++++++++++++++++++++
 

MANIFEST.in

@@ -0,0 +1,23 @@
+include setup.py
+
+include *.txt
+include *.yml
+recursive-include executable *.ico
+recursive-include executable *.py
+requirements.txt
+recursive-include executable *.spec
+
+exclude tests/.coverage
+global-exclude *.xml
+
+global-exclude *.py[cod] __pycache__/* *.so *.dylib
+
+# added by check-manifest
+include *.py
+
+exclude setup.py
+
+# added by check-manifest
+include *.in
+
+exclude MANIFEST.in

docs/bdew.rst

@@ -65,6 +65,12 @@ The parameter ``building_class`` (German: Baualtersklasse) can assume values in
 Usage
 +++++
 
+.. code-block:: python
+
+    from demandlib import bdew
+
+    ...
+
 Electrical Profiles
 ~~~~~~~~~~~~~~~~~~~
 
@@ -74,7 +80,7 @@ Description
 The electrical profiles are the standard load profiles from BDEW. All profiles
 have a resolution of 15 minutes. They are based on measurements in the German
 electricity sector. There is a dynamic function (h0_dyn) for the houshold (h0)
-profile that better takes the seasonal variance into account.
+profile that better takes the seasonal variance into account [`BDEW <https://www.bdew.de/energie/standardlastprofile-strom/>`_].
 
 .. math::
 
@@ -85,7 +91,7 @@ With `t` the day of the year as a decimal number.
 The following profile types are available.
 Be aware that the types in Python code are strings in **lowercase**.
 
-.. csv-table:: German (original)
+.. csv-table:: German (original) [`Wikipedia <https://de.wikipedia.org/wiki/Standardlastprofil>`_]
    :header: Typ,Beschreibung,Erläuterung
    :widths: 10, 40, 50
 
@@ -130,3 +136,27 @@ Usage
 .. code-block:: python
 
     from demandlib import bdew
+    e_slp = bdew.ElecSlp(year=2020)
+
+    # get all available types
+    print(e_slp.get_profiles().columns)
+
+    # get the "h0" and "g0" profile
+    profiles = e_slp.get_profiles("h0", "g0")
+
+    # get scaled profiles
+    scaled_profiles = e_slp.get_scaled_profiles({"h0": 3000, "g0": 5000})
+
+    # get scaled profiles with power values instead of energy values
+    # a conversion_factor of 4 will convert Wh, kWh etc. to W, kW
+    e_slp.get_scaled_power_profiles({"h0": 3000, "g0": 5000}, conversion_factor=4)
+
+    # add holidays, holidays are treated as Sundays
+    holidays = {
+        datetime.date(2010, 1, 1): "New year",
+        datetime.date(2010, 10, 3): "Day of German Unity",
+    }
+    e_slp = bdew.ElecSlp(year=2010, holidays=holidays)
+
+    # holiday dictionaries can be created using workalendar
+    # https://github.com/workalendar/workalendar

docs/index.rst

@@ -8,6 +8,7 @@ Contents
    readme
    installation
    bdew
+   vdi4655
    further_profiles
    reference/index
    contributing

docs/reference/index.rst

@@ -6,14 +6,22 @@ Reference
     :undoc-members:
     :show-inheritance:
 
-
 .. automodule:: demandlib.bdew.heat_building
     :members:
     :undoc-members:
     :show-inheritance:
 
-
 .. automodule:: demandlib.particular_profiles
     :members:
     :undoc-members:
     :show-inheritance:
+
+.. automodule:: demandlib.vdi.regions
+    :members:
+    :undoc-members:
+    :show-inheritance:
+
+.. automodule:: demandlib.vdi.dwd_try
+    :members:
+    :undoc-members:
+    :show-inheritance:

docs/vdi4655.rst

@@ -0,0 +1,93 @@
+=====================
+VDI4655 Load Profiles
+=====================
+
+Overview
+--------
+
+The VDI 4655 module implements load profile generation for residential buildings
+according to the German engineering standard VDI 4655. Heat and power demand
+profiles are generated based on typical days and building characteristics.
+
+Key Features:
+
+* Generates heating, hot water and power demand profiles for residential buildings
+* Supports both single-family (EFH) and multi-family houses (MFH)
+* Considers weather data, based on the building location in Germany
+* Accounts for seasonal variations and holidays
+* Customizable temperature limits for season definitions
+* Adjustable temporal resolution (e.g., hourly, 15-minute intervals)
+
+
+Example Usage
+-------------
+
+Here's a basic example of how to use the VDI 4655 module::
+
+    from demandlib import vdi
+
+    # Define houses
+    houses = [
+        {
+            "name": "EFH_1",
+            "house_type": "EFH",
+            "N_Pers": 3,
+            "N_WE": 1,
+            "Q_Heiz_a": 6000,
+            "Q_TWW_a": 1500,
+            "W_a": 5250,
+        }
+    ]
+
+    # Create region
+    region = vdi.Region(
+        2017,
+        try_region=4,
+        houses=houses,
+        resample_rule="1h"
+    )
+
+    # Generate load curves
+    load_curves = region.get_load_curve_houses()
+
+House Parameters
+----------------
+
+Required parameters for each house:
+
+* ``name``: Unique identifier for the house
+* ``house_type``: Either "EFH" (single-family) or "MFH" (multi-family)
+* ``N_Pers``: Number of persons, up to 12 (relevant for EFH)
+* ``N_WE``: Number of apartments, up to 40 (relevant for MFH)
+* ``Q_Heiz_a``: Annual heating demand in kWh
+* ``Q_TWW_a``: Annual hot water demand in kWh
+* ``W_a``: Annual electricity demand in kWh
+
+Optional parameters:
+
+* ``summer_temperature_limit``: Temperature threshold for summer season (default: 15°C)
+* ``winter_temperature_limit``: Temperature threshold for winter season (default: 5°C)
+
+Weather Data
+------------
+
+The module uses German test reference year (TRY) weather data by 'Deutscher Wetterdienst' (DWD)
+for determining the daily temperature and cloud coverage. You can:
+
+* Use the weather data from one of the 15 TRY regions by DWD from 2010
+
+  * Specify a TRY region number (``try_region`` parameter), or
+
+  * Use geographical coordinates to determine the TRY region (requires geopandas)
+
+* Provide your own weather file (``file_weather`` parameter), adhering to the standard
+  of the TRY weather data published in 2016 by DWD (available at https://kunden.dwd.de/obt/)
+
+Further Reading
+---------------
+
+For more details about the VDI 4655 standard, refer to:
+
+* VDI 4655: Reference load profiles of single-family and multi-family houses for the use of CHP systems
+* May 2008 (ICS 91.140.01)
+* Verein Deutscher Ingenieure e.V.

examples/bdew_slp25.py

@@ -0,0 +1,50 @@
+"""
+SPDX-FileCopyrightText: Deutsches Zentrum für Luft- und Raumfahrt
+SPDX-FileCopyrightText: Patrik Schönfeldt
+
+
+SPDX-License-Identifier: MIT
+"""
+
+import datetime
+
+import matplotlib.pyplot as plt
+import pandas as pd
+
+
+from demandlib import bdew
+
+index15m = pd.date_range(
+    start="2020-01-01 00:00",
+    end="2020-01-31 23:45",
+    freq="15min",
+)
+index1m = pd.date_range(
+    start="2020-01-01 00:00",
+    end="2020-01-31 23:45",
+    freq="1min",
+)
+index3h = pd.date_range(
+    start="2020-01-01 00:00",
+    end="2020-01-31 23:45",
+    freq="3h",
+)
+
+holidays = [
+    datetime.date(2020, 1, 1),
+    datetime.date(2020, 1, 2),
+    datetime.date(2020, 1, 3),
+    datetime.date(2020, 1, 4),
+    datetime.date(2020, 1, 5),
+]
+
+h25_holidays = bdew.H25(index1m, holidays)
+h25_std = bdew.H25(index15m)
+h25_3h = bdew.H25(index3h)
+
+plt.step(h25_holidays.index, h25_holidays, label="Holidays", where="post")
+plt.step(h25_std.index, h25_std, label="Standard", where="post")
+plt.step(h25_3h.index, h25_3h, label="Three hours", where="post")
+plt.legend()
+
+plt.show()

examples/electricity_demand_example.py

@@ -28,7 +28,7 @@
 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()
@@ -62,7 +62,7 @@
 e_slp = bdew.ElecSlp(year, holidays=holidays)
 
 # multiply given annual demand with timeseries
-elec_demand = e_slp.get_profile(ann_el_demand_per_sector)
+elec_demand = e_slp.get_scaled_power_profiles(ann_el_demand_per_sector)
 
 # Add the slp for the industrial group
 ilp = profiles.IndustrialLoadProfile(e_slp.date_time_index, holidays=holidays)