Merge pull request #160 from davidusb-geek/davidusb-geek/dev/new_ver_0p7

Feat - Prepared new version, see CHANGELOG

.github/workflows/publish_docker.yaml

@@ -11,7 +11,7 @@ jobs:
     runs-on: ubuntu-latest
     steps:
       - name: Checkout the repository
-        uses: actions/checkout@v3
+        uses: actions/checkout@v4
       - name: Docker meta
         id: meta
         uses: docker/metadata-action@v4

.github/workflows/python-test.yml

@@ -22,10 +22,10 @@ jobs:
       PYTHON: ${{ matrix.python-version }}
 
     steps:
-    - uses: actions/checkout@v3
+    - uses: actions/checkout@v4
 
     - name: Set up Python ${{ matrix.python-version }}
-      uses: actions/setup-python@v4
+      uses: actions/setup-python@v5
       with:
         python-version: ${{ matrix.python-version }}
 

.vscode/launch.json

@@ -1,20 +1,28 @@
 {
   "configurations": [
     {
-        "name": "EMHASS run",
-        "type": "python",
-        "request": "launch",
-        "program": "web_server.py",
-        "console": "integratedTerminal",
-        "cwd": "${workspaceFolder}/src/emhass/",
-        "purpose":["debug-in-terminal"],
-        "justMyCode": true,
-        "env": {
-          "CONFIG_PATH": "/workspaces/emhass/config_emhass.yaml",
-          "OPTIONS_PATH": "/workspaces/emhass/options.json",
-          "SECRETS_PATH": "/workspaces/emhass/secrets_emhass.yaml",
-          "DATA_PATH": "/workspaces/emhass/data/",
-        }
+      "name": "Python: Current File",
+      "type": "python",
+      "request": "launch",
+      "program": "${file}",
+      "console": "integratedTerminal",
+      "justMyCode": true
+    },
+    {
+      "name": "EMHASS run",
+      "type": "python",
+      "request": "launch",
+      "program": "web_server.py",
+      "console": "integratedTerminal",
+      "cwd": "${workspaceFolder}/src/emhass/",
+      "purpose":["debug-in-terminal"],
+      "justMyCode": true,
+      "env": {
+        "CONFIG_PATH": "/workspaces/emhass/config_emhass.yaml",
+        "OPTIONS_PATH": "/workspaces/emhass/options.json",
+        "SECRETS_PATH": "/workspaces/emhass/secrets_emhass.yaml",
+        "DATA_PATH": "/workspaces/emhass/data/",
+      }
     },
     {
       "name": "EMHASS run ADDON",

CHANGELOG.md

@@ -1,5 +1,19 @@
 # Changelog
 
+## [0.7.0] - 2024-01-28
+### Improvement
+- Added a new feature to provide operating time windows for deferrable loads. Thanks to @michaelpiron
+- Added lots of new options to be configured by the user. Thanks to @GeoDerp
+- Updated stylesheet with mobile & dark theme by @GeoDerp
+- Improved launch.json to fully test EMHASS on different configurations. Thanks to @GeoDerp
+- Added new script to debug and develop new time series clustering feature
+- Improved documentation. Thanks to @g1za
+### Fix
+- Updated github workflow actions/checkout to v4 and actions/setup-python to v5
+- Changed default values for weight_battery_discharge and weight_battery_charge to zero
+- Renamed classes to conform to PEP8
+- Bump markupsafe from 2.1.3 to 2.1.4 
+
 ## [0.6.2] - 2024-01-04
 ### Improvement
 - Added option to pass additional weight for battery usage

config_emhass.yaml

@@ -58,8 +58,8 @@ optim_conf:
   set_battery_dynamic: False # add a constraint to limit the dynamic of the battery power in power per time unit
   battery_dynamic_max: 0.9 # maximum dynamic positive power variation in percentage of battery maximum power
   battery_dynamic_min: -0.9 # minimum dynamic negative power variation in percentage of battery maximum power
-  weight_battery_discharge: 1.0 # weight applied in cost function to battery usage for discharge
-  weight_battery_charge: 1.0 # weight applied in cost function to battery usage for charge
+  weight_battery_discharge: 0.0 # weight applied in cost function to battery usage for discharge
+  weight_battery_charge: 0.0 # weight applied in cost function to battery usage for charge
 
 plant_conf:
   P_grid_max: 9000 # The maximum power that can be supplied by the utility grid in Watts

docs/conf.py

@@ -22,7 +22,7 @@
 author = 'David HERNANDEZ'
 
 # The full version, including alpha/beta/rc tags
-release = '0.6.2'
+release = '0.7.0'
 
 # -- General configuration ---------------------------------------------------
 

requirements.txt

@@ -1,7 +1,7 @@
 wheel
 numpy<=1.26.0
-pandas<=2.0.3
 scipy<=1.11.3
+pandas<=2.0.3
 pvlib>=0.10.2
 protobuf>=3.0.0
 pytz>=2021.1

scripts/load_clustering.py

@@ -9,8 +9,8 @@
 pio.renderers.default = 'browser'
 pd.options.plotting.backend = "plotly"
 
-from emhass.retrieve_hass import retrieve_hass
-from emhass.forecast import forecast
+from emhass.retrieve_hass import RetrieveHass
+from emhass.forecast import Forecast
 from emhass.utils import get_root, get_yaml_parse, get_days_list, get_logger
 
 from sklearn.cluster import KMeans
@@ -55,7 +55,7 @@
     else:
         logger.info("Using EMHASS methods to retrieve the new forecast model train data")
         retrieve_hass_conf, _, _ = get_yaml_parse(pathlib.Path(root+'/config_emhass.yaml'), use_secrets=True)
-        rh = retrieve_hass(retrieve_hass_conf['hass_url'], retrieve_hass_conf['long_lived_token'], 
+        rh = RetrieveHass(retrieve_hass_conf['hass_url'], retrieve_hass_conf['long_lived_token'], 
         retrieve_hass_conf['freq'], retrieve_hass_conf['time_zone'],
         params, root, logger, get_data_from_file=False)
 

scripts/load_forecast_sklearn.py

@@ -8,8 +8,8 @@
 pio.renderers.default = 'browser'
 pd.options.plotting.backend = "plotly"
 
-from emhass.retrieve_hass import retrieve_hass
-from emhass.forecast import forecast
+from emhass.retrieve_hass import RetrieveHass
+from emhass.forecast import Forecast
 from emhass.utils import get_root, get_yaml_parse, get_days_list, get_logger
 
 from sklearn.linear_model import LinearRegression
@@ -63,7 +63,7 @@ def neg_r2_score(y_true, y_pred):
     else:
         logger.info("Using EMHASS methods to retrieve the new forecast model train data")
         retrieve_hass_conf, _, _ = get_yaml_parse(pathlib.Path(root+'/config_emhass.yaml'), use_secrets=True)
-        rh = retrieve_hass(retrieve_hass_conf['hass_url'], retrieve_hass_conf['long_lived_token'], 
+        rh = RetrieveHass(retrieve_hass_conf['hass_url'], retrieve_hass_conf['long_lived_token'], 
         retrieve_hass_conf['freq'], retrieve_hass_conf['time_zone'],
         params, root, logger, get_data_from_file=False)
 
@@ -240,14 +240,14 @@ def neg_r2_score(y_true, y_pred):
 
     # Let's perform a naive load forecast for comparison
     retrieve_hass_conf, optim_conf, plant_conf = get_yaml_parse(pathlib.Path(root+'/config_emhass.yaml'), use_secrets=True)
-    fcst = forecast(retrieve_hass_conf, optim_conf, plant_conf,
+    fcst = Forecast(retrieve_hass_conf, optim_conf, plant_conf,
                     params, root, logger)
     P_load_forecast = fcst.get_load_forecast(method='naive')
 
     # Then retrieve some data and perform a prediction mocking a production env
-    rh = retrieve_hass(retrieve_hass_conf['hass_url'], retrieve_hass_conf['long_lived_token'], 
-        retrieve_hass_conf['freq'], retrieve_hass_conf['time_zone'],
-        params, root, logger, get_data_from_file=False)
+    rh = RetrieveHass(retrieve_hass_conf['hass_url'], retrieve_hass_conf['long_lived_token'], 
+                      retrieve_hass_conf['freq'], retrieve_hass_conf['time_zone'],
+                      params, root, logger, get_data_from_file=False)
 
     days_list = get_days_list(days_needed)
     var_model = retrieve_hass_conf['var_load']

scripts/optim_results_analysis.py

@@ -9,9 +9,9 @@
 pio.renderers.default = 'browser'
 pd.options.plotting.backend = "plotly"
 
-from emhass.retrieve_hass import retrieve_hass
-from emhass.optimization import optimization
-from emhass.forecast import forecast
+from emhass.retrieve_hass import RetrieveHass
+from emhass.optimization import Optimization
+from emhass.forecast import Forecast
 from emhass.utils import get_root, get_yaml_parse, get_days_list, get_logger
 
 # the root folder
@@ -21,14 +21,14 @@
 
 def get_forecast_optim_objects(retrieve_hass_conf, optim_conf, plant_conf,
                                params, get_data_from_file):
-    fcst = forecast(retrieve_hass_conf, optim_conf, plant_conf,
+    fcst = Forecast(retrieve_hass_conf, optim_conf, plant_conf,
                     params, root, logger, get_data_from_file=get_data_from_file)
     df_weather = fcst.get_weather_forecast(method=optim_conf['weather_forecast_method'])
     P_PV_forecast = fcst.get_power_from_weather(df_weather)
     P_load_forecast = fcst.get_load_forecast(method=optim_conf['load_forecast_method'])
     df_input_data_dayahead = pd.concat([P_PV_forecast, P_load_forecast], axis=1)
     df_input_data_dayahead.columns = ['P_PV_forecast', 'P_load_forecast']
-    opt = optimization(retrieve_hass_conf, optim_conf, plant_conf, 
+    opt = Optimization(retrieve_hass_conf, optim_conf, plant_conf, 
                        fcst.var_load_cost, fcst.var_prod_price,  
                        'profit', root, logger)
     return fcst, P_PV_forecast, P_load_forecast, df_input_data_dayahead, opt
@@ -41,9 +41,9 @@ def get_forecast_optim_objects(retrieve_hass_conf, optim_conf, plant_conf,
     retrieve_hass_conf, optim_conf, plant_conf = get_yaml_parse(pathlib.Path(root+'/config_emhass.yaml'), use_secrets=False)
     retrieve_hass_conf, optim_conf, plant_conf = \
         retrieve_hass_conf, optim_conf, plant_conf
-    rh = retrieve_hass(retrieve_hass_conf['hass_url'], retrieve_hass_conf['long_lived_token'], 
-                        retrieve_hass_conf['freq'], retrieve_hass_conf['time_zone'],
-                        params, root, logger)
+    rh = RetrieveHass(retrieve_hass_conf['hass_url'], retrieve_hass_conf['long_lived_token'], 
+                      retrieve_hass_conf['freq'], retrieve_hass_conf['time_zone'],
+                      params, root, logger)
     if get_data_from_file:
         with open(pathlib.Path(root+'/data/test_df_final.pkl'), 'rb') as inp:
             rh.df_final, days_list, var_list = pickle.load(inp)

scripts/special_config_analysis.py

@@ -19,9 +19,9 @@
 pio.renderers.default = 'browser'
 pd.options.plotting.backend = "plotly"
 
-from emhass.retrieve_hass import retrieve_hass
-from emhass.optimization import optimization
-from emhass.forecast import forecast
+from emhass.retrieve_hass import RetrieveHass
+from emhass.optimization import Optimization
+from emhass.forecast import Forecast
 from emhass.utils import get_root, get_yaml_parse, get_days_list, get_logger
 
 # the root folder
@@ -31,14 +31,14 @@
 
 def get_forecast_optim_objects(retrieve_hass_conf, optim_conf, plant_conf,
                                params, get_data_from_file):
-    fcst = forecast(retrieve_hass_conf, optim_conf, plant_conf,
+    fcst = Forecast(retrieve_hass_conf, optim_conf, plant_conf,
                     params, root, logger, get_data_from_file=get_data_from_file)
     df_weather = fcst.get_weather_forecast(method='solar.forecast')
     P_PV_forecast = fcst.get_power_from_weather(df_weather)
     P_load_forecast = fcst.get_load_forecast(method=optim_conf['load_forecast_method'])
     df_input_data_dayahead = pd.concat([P_PV_forecast, P_load_forecast], axis=1)
     df_input_data_dayahead.columns = ['P_PV_forecast', 'P_load_forecast']
-    opt = optimization(retrieve_hass_conf, optim_conf, plant_conf, 
+    opt = Optimization(retrieve_hass_conf, optim_conf, plant_conf, 
                        fcst.var_load_cost, fcst.var_prod_price,  
                        'cost', root, logger)
     return fcst, P_PV_forecast, P_load_forecast, df_input_data_dayahead, opt
@@ -152,9 +152,9 @@ def build_params(params, options):
     else:
 
         retrieve_hass_conf, optim_conf, plant_conf = get_yaml_parse(config_path, use_secrets=True, params = json.dumps(params))
-        rh = retrieve_hass(retrieve_hass_conf['hass_url'], retrieve_hass_conf['long_lived_token'], 
-                            retrieve_hass_conf['freq'], retrieve_hass_conf['time_zone'],
-                            params, root, logger)
+        rh = RetrieveHass(retrieve_hass_conf['hass_url'], retrieve_hass_conf['long_lived_token'], 
+                          retrieve_hass_conf['freq'], retrieve_hass_conf['time_zone'],
+                          params, root, logger)
         days_list = get_days_list(retrieve_hass_conf['days_to_retrieve'])
         var_list = [retrieve_hass_conf['var_load'], retrieve_hass_conf['var_PV']]
         rh.get_data(days_list, var_list,

scripts/use_cases_analysis.py

@@ -16,9 +16,9 @@
 pio.renderers.default = 'browser'
 pd.options.plotting.backend = "plotly"
 
-from emhass.retrieve_hass import retrieve_hass
-from emhass.optimization import optimization
-from emhass.forecast import forecast
+from emhass.retrieve_hass import RetrieveHass
+from emhass.optimization import Optimization
+from emhass.forecast import Forecast
 from emhass.utils import get_root, get_yaml_parse, get_days_list, get_logger
 
 # the root folder
@@ -28,14 +28,14 @@
 
 def get_forecast_optim_objects(retrieve_hass_conf, optim_conf, plant_conf,
                                params, get_data_from_file):
-    fcst = forecast(retrieve_hass_conf, optim_conf, plant_conf,
+    fcst = Forecast(retrieve_hass_conf, optim_conf, plant_conf,
                     params, root, logger, get_data_from_file=get_data_from_file)
     df_weather = fcst.get_weather_forecast(method='solar.forecast')
     P_PV_forecast = fcst.get_power_from_weather(df_weather)
     P_load_forecast = fcst.get_load_forecast(method=optim_conf['load_forecast_method'])
     df_input_data_dayahead = pd.concat([P_PV_forecast, P_load_forecast], axis=1)
     df_input_data_dayahead.columns = ['P_PV_forecast', 'P_load_forecast']
-    opt = optimization(retrieve_hass_conf, optim_conf, plant_conf, 
+    opt = Optimization(retrieve_hass_conf, optim_conf, plant_conf, 
                        fcst.var_load_cost, fcst.var_prod_price,  
                        'profit', root, logger)
     return fcst, P_PV_forecast, P_load_forecast, df_input_data_dayahead, opt
@@ -45,9 +45,9 @@ def get_forecast_optim_objects(retrieve_hass_conf, optim_conf, plant_conf,
     params = None
     save_figures = False
     retrieve_hass_conf, optim_conf, plant_conf = get_yaml_parse(pathlib.Path(root+'/config_emhass.yaml'), use_secrets=True)
-    rh = retrieve_hass(retrieve_hass_conf['hass_url'], retrieve_hass_conf['long_lived_token'], 
-                        retrieve_hass_conf['freq'], retrieve_hass_conf['time_zone'],
-                        params, root, logger)
+    rh = RetrieveHass(retrieve_hass_conf['hass_url'], retrieve_hass_conf['long_lived_token'], 
+                      retrieve_hass_conf['freq'], retrieve_hass_conf['time_zone'],
+                      params, root, logger)
     days_list = get_days_list(retrieve_hass_conf['days_to_retrieve'])
     var_list = [retrieve_hass_conf['var_load'], retrieve_hass_conf['var_PV']]
     rh.get_data(days_list, var_list,

setup.py

@@ -19,7 +19,7 @@
 
 setup(
     name='emhass',  # Required
-    version='0.6.2',  # Required
+    version='0.7.0',  # Required
     description='An Energy Management System for Home Assistant',  # Optional
     long_description=long_description,  # Optional
     long_description_content_type='text/markdown',  # Optional (see note above)
@@ -31,7 +31,7 @@
         'Intended Audience :: Developers',
         'Topic :: Software Development :: Build Tools',
         'License :: OSI Approved :: MIT License',
-        'Programming Language :: Python :: 3.10',
+        'Programming Language :: Python :: 3.11',
         "Operating System :: OS Independent",
     ],
     keywords='energy, management, optimization, hass',  # Optional
@@ -43,15 +43,19 @@
         'numpy<=1.26',
         'scipy<=1.11.3',
         'pandas<=2.0.3',
-        'pvlib>=0.10.1',
+        'pvlib>=0.10.2',
         'protobuf>=3.0.0',
         'pytz>=2021.1',
         'requests>=2.25.1',
         'beautifulsoup4>=4.9.3',
+        'h5py==3.10.0',
         'pulp>=2.4',
         'pyyaml>=5.4.1',
         'tables<=3.9.1',
         'skforecast==0.11.0',
+        'flask>=2.0.3',
+        'waitress>=2.1.1',
+        'plotly>=5.6.0'
     ],  # Optional
     entry_points={  # Optional
         'console_scripts': [