Added an open_meteo_cache_max_age config option to control Open-Meteo JSON reponse caching

Author: paulhomes

docs/forecasts.md

@@ -94,6 +94,18 @@ curl -i -H 'Content-Type:application/json' -X POST -d {} http://localhost:5000/a
 curl -i -H 'Content-Type:application/json' -X POST -d '{"weather_forecast_cache_only":true}' http://localhost:5000/action/naive-mpc-optim
 ```
 
+#### Caching Open-Meteo Weather Service Usage
+
+When you have EMHASS configured to use the Open-Meteo weather service, to minimize API calls to the service, and to provide
+resilience in case of transient connectivity issues, EMHASS caches successful calls to the Open-Meteo API in a
+`cached-open-meteo-forecast.json` file in the data directory. The JSON file contains the default 3 days of weather forecast data.
+This Open-Meteo cache is independent of the PV cache discussed above and will be used even when the PV cache is not enabled.
+By default, when the JSON file is older than 30 minutes, attempts will be made to replace it with a more recent version
+from the Open-Meteo weather service. It will only be replaced if this is successful. If any errors occur the older version
+will continue to be used until a new version can been fetched. The maximum cache age, with a default value of 30 minutes, can be
+configured using the `open_meteo_cache_max_age` setting in config.json or as a parameter in EMHASS REST API calls.
+The value is specified in minutes. If you want to disable caching you can specify a value of 0.
+
 #### Adjusting PV Forecasts using machine learning
 EMHASS provides methods to adjust the PV power forecast using machine learning regression techniques. The adjustment process consists of two steps: training a regression model using historical PV data and then applying the trained model to correct new PV forecasts.
 

src/emhass/data/associations.csv

@@ -46,6 +46,7 @@ optim_conf,battery_dynamic_min,battery_dynamic_min
 optim_conf,weight_battery_discharge,weight_battery_discharge
 optim_conf,weight_battery_charge,weight_battery_charge
 optim_conf,weather_forecast_method,weather_forecast_method
+optim_conf,open_meteo_cache_max_age,open_meteo_cache_max_age
 optim_conf,def_start_timestep,start_timesteps_of_each_deferrable_load,list_start_timesteps_of_each_deferrable_load
 optim_conf,def_end_timestep,end_timesteps_of_each_deferrable_load,list_end_timesteps_of_each_deferrable_load
 optim_conf,list_hp_periods,load_peak_hour_periods

src/emhass/data/config_defaults.json

@@ -43,6 +43,7 @@
     0
   ],
   "weather_forecast_method": "open-meteo",
+  "open_meteo_cache_max_age": 30,
   "load_forecast_method": "naive",
   "delta_forecast_daily": 1,
   "load_cost_forecast_method": "hp_hc_periods",

src/emhass/forecast.py

@@ -335,7 +335,7 @@ def get_weather_forecast(
             method == "open-meteo" or method == "scrapper"
         ):  # The scrapper option is being left here for backward compatibility
             if not os.path.isfile(w_forecast_cache_path):
-                data_raw = self.get_cached_open_meteo_forecast_json()
+                data_raw = self.get_cached_open_meteo_forecast_json(self.optim_conf["open_meteo_cache_max_age"])
                 data_15min = pd.DataFrame.from_dict(data_raw["minutely_15"])
                 data_15min["time"] = pd.to_datetime(data_15min["time"])
                 data_15min.set_index("time", inplace=True)

src/emhass/static/data/param_definitions.json

@@ -150,6 +150,12 @@
       ],
       "default_value": "open-meteo"
     },
+    "open_meteo_cache_max_age": {
+      "friendly_name": "Open-Meteo Cache Max Age",
+      "Description": "The maximum age, in minutes, of the cached open-meteo json response, after which a new version will be fetched from Open-Meteo. Defaults to 30.",
+      "input": "int",
+      "default_value": 30
+    },
     "maximum_power_from_grid": {
       "friendly_name": "Max power from grid",
       "Description": "The maximum power that can be supplied by the utility grid in Watts (consumption). Defaults to 9000.",