Modified LP solver parameter implementation and prepared new version

CHANGELOG.md

@@ -4,6 +4,10 @@ All notable changes to this project will be documented in this file.
 The format is based on [Keep a Changelog](https://keepachangelog.com/en/1.0.0/),
 and this project adheres to [Semantic Versioning](https://semver.org/spec/v2.0.0.html).
 
+## [0.3.11] - 2022-05-23
+### Improvement
+- Added support to provide solver name and path as parameters in the configuration file.
+
 ## [0.3.11] - 2022-05-23
 ### Fix
 - Fixed unittests not passing.

config_emhass.yaml

@@ -45,6 +45,8 @@ optim_conf:
   - prod_price_forecast_method: 'constant' # options are 'constant' for constant fixed value or 'csv' to load custom price forecast from a CSV file
   - prod_sell_price: 0.065 # power production selling price in €/kWh (only needed if prod_price_forecast_method='constant')
   - set_total_pv_sell: False # consider that all PV power is injected to the grid (self-consumption with total sell)
+  - lp_solver: 'PULP_CBC_CMD' # set the name of the linear programming solver that will be used
+  - lp_solver_path: '/usr/bin/cbc' # set the path to the LP solver
 
 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 = '0.3.11'
+release = '0.3.12'
 
 # -- General configuration ---------------------------------------------------
 

docs/config.md

@@ -71,6 +71,8 @@ The following parameters and definitions are only needed if load_cost_forecast_m
 
 - prod_price_forecast_method: Define the method that will be used for PV power production price forecast. This is the price that is payed by the utility for energy injected to the grid. The options are 'constant' for a constant fixed value or 'csv' to load custom price forecast from a CSV file. The default CSV file path that will be used is '/data/data_prod_price_forecast.csv'.
 - prod_sell_price: The paid price for energy injected to the grid from excedent PV production in €/kWh. Defaults to 0.065. This parameter is only needed if prod_price_forecast_method='constant'.
+- lp_solver: Set the name of the linear programming solver that will be used. Defaults to 'PULP_CBC_CMD'.
+- lp_solver_path: Set the path to the LP solver. Defaults to '/usr/bin/cbc'.
 
 ## System configuration parameters
 

setup.py

@@ -19,7 +19,7 @@
 
 setup(
     name='emhass',  # Required
-    version='0.3.11',  # Required
+    version='0.3.12',  # 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)

src/emhass/optimization.py

@@ -27,8 +27,7 @@ class optimization:
     def __init__(self, retrieve_hass_conf: dict, optim_conf: dict, plant_conf: dict, 
                  var_load_cost: str, var_prod_price: str, days_list: pd.date_range, 
                  costfun: str, config_path: str, logger: logging.Logger, 
-                 opt_time_delta: Optional[int] = 24, lp_solver: Optional[str] = 'PULP_CBC_CMD',
-                 lp_solver_path: Optional[str] = '/usr/bin/cbc') -> None:
+                 opt_time_delta: Optional[int] = 24) -> None:
         """
         Define constructor for optimization class.
         
@@ -58,10 +57,6 @@ def __init__(self, retrieve_hass_conf: dict, optim_conf: dict, plant_conf: dict,
             more than one day then the optimization will be peformed by chunks of \
             opt_time_delta periods, defaults to 24
         :type opt_time_delta: float, optional
-        :param lp_solver: The linear programming solver name to use
-        :type lp_solver: str, optional
-        :param lp_solver_path: The path to the solver name to use
-        :type lp_solver_path: str, optional
         
         """
         self.retrieve_hass_conf = retrieve_hass_conf
@@ -79,8 +74,16 @@ def __init__(self, retrieve_hass_conf: dict, optim_conf: dict, plant_conf: dict,
         self.logger = logger
         self.var_load_cost = var_load_cost
         self.var_prod_price = var_prod_price
-        self.lp_solver = lp_solver
-        self.lp_solver_path = lp_solver_path
+        if 'lp_solver' in optim_conf.keys():
+            self.lp_solver = optim_conf['lp_solver']
+        else:
+            self.lp_solver = 'PULP_CBC_CMD'
+        if 'lp_solver_path' in optim_conf.keys():
+            self.lp_solver_path = optim_conf['lp_solver_path']
+        else:
+            self.lp_solver_path = r'/usr/bin/cbc'
+        if self.lp_solver != 'COIN_CMD' and 'lp_solver_path' in optim_conf.keys():
+            self.logger.error("Use COIN_CMD solver name if you want to set a path for the LP solver")
 
     def perform_optimization(self, data_opt: pd.DataFrame, P_PV: np.array, P_load: np.array, 
                              unit_load_cost: np.array, unit_prod_price: np.array,

src/emhass/web_server.py

@@ -80,6 +80,8 @@ def build_params(params, options, addon):
         params['optim_conf'][12]['load_cost_hc'] = options['load_offpeak_hours_cost']
         params['optim_conf'][14]['prod_sell_price'] = options['photovoltaic_production_sell_price']
         params['optim_conf'][15]['set_total_pv_sell'] = options['set_total_pv_sell']
+        params['optim_conf'][16]['lp_solver'] = options['lp_solver']
+        params['optim_conf'][17]['lp_solver_path'] = options['lp_solver_path']
         # Updating variables in plant_conf
         params['plant_conf'][0]['P_grid_max'] = options['maximum_power_from_grid']
         params['plant_conf'][1]['module_model'] = [i['pv_module_model'] for i in options['list_pv_module_model']]