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feat: add Home Assistant and NodeRED adapters (#764)

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Adapters for Home Assistant and NodeRED integration are added.
Akkudoktor-EOS can now be run as Home Assistant add-on and standalone.

As Home Assistant add-on EOS uses ingress to fully integrate the EOSdash dashboard
in Home Assistant.

The fix includes several bug fixes that are not directly related to the adapter
implementation but are necessary to keep EOS running properly and to test and
document the changes.

* fix: development version scheme

  The development versioning scheme is adaptet to fit to docker and
  home assistant expectations. The new scheme is x.y.z and x.y.z.dev<hash>.
  Hash is only digits as expected by home assistant. Development version
  is appended by .dev as expected by docker.

* fix: use mean value in interval on resampling for array

  When downsampling data use the mean value of all values within the new
  sampling interval.

* fix: default battery ev soc and appliance wh

  Make the genetic simulation return default values for the
  battery SoC, electric vehicle SoC and appliance load if these
  assets are not used.

* fix: import json string

  Strip outer quotes from JSON strings on import to be compliant to json.loads()
  expectation.

* fix: default interval definition for import data

  Default interval must be defined in lowercase human definition to
  be accepted by pendulum.

* fix: clearoutside schema change

* feat: add adapters for integrations

  Adapters for Home Assistant and NodeRED integration are added.
  Akkudoktor-EOS can now be run as Home Assistant add-on and standalone.

  As Home Assistant add-on EOS uses ingress to fully integrate the EOSdash dashboard
  in Home Assistant.

* feat: allow eos to be started with root permissions and drop priviledges

  Home assistant starts all add-ons with root permissions. Eos now drops
  root permissions if an applicable user is defined by paramter --run_as_user.
  The docker image defines the user eos to be used.

* feat: make eos supervise and monitor EOSdash

  Eos now not only starts EOSdash but also monitors EOSdash during runtime
  and restarts EOSdash on fault. EOSdash logging is captured by EOS
  and forwarded to the EOS log to provide better visibility.

* feat: add duration to string conversion

  Make to_duration to also return the duration as string on request.

* chore: Use info logging to report missing optimization parameters

  In parameter preparation for automatic optimization an error was logged for missing paramters.
  Log is now down using the info level.

* chore: make EOSdash use the EOS data directory for file import/ export

  EOSdash use the EOS data directory for file import/ export by default.
  This allows to use the configuration import/ export function also
  within docker images.

* chore: improve EOSdash config tab display

  Improve display of JSON code and add more forms for config value update.

* chore: make docker image file system layout similar to home assistant

  Only use /data directory for persistent data. This is handled as a
  docker volume. The /data volume is mapped to ~/.local/share/net.akkudoktor.eos
  if using docker compose.

* chore: add home assistant add-on development environment

  Add VSCode devcontainer and task definition for home assistant add-on
  development.

* chore: improve documentation
This commit is contained in:
Bobby Noelte
2025-12-30 22:08:21 +01:00
committed by GitHub
parent 02c794460f
commit 58d70e417b
111 changed files with 6815 additions and 1199 deletions
Download Patch File Download Diff File Expand all files Collapse all files

67
src/akkudoktoreos/optimization/genetic/geneticparams.py
View File

@@ -177,33 +177,33 @@ class GeneticOptimizationParameters(
# Check for general predictions conditions
if cls.config.general.latitude is None:
default_latitude = 52.52
logger.error(f"Latitude unknown - defaulting to {default_latitude}.")
logger.info(f"Latitude unknown - defaulting to {default_latitude}.")
cls.config.general.latitude = default_latitude
if cls.config.general.longitude is None:
default_longitude = 13.405
logger.error(f"Longitude unknown - defaulting to {default_longitude}.")
logger.info(f"Longitude unknown - defaulting to {default_longitude}.")
cls.config.general.longitude = default_longitude
if cls.config.prediction.hours is None:
logger.error("Prediction hours unknown - defaulting to 48 hours.")
logger.info("Prediction hours unknown - defaulting to 48 hours.")
cls.config.prediction.hours = 48
if cls.config.prediction.historic_hours is None:
logger.error("Prediction historic hours unknown - defaulting to 24 hours.")
logger.info("Prediction historic hours unknown - defaulting to 24 hours.")
cls.config.prediction.historic_hours = 24
# Check optimization definitions
if cls.config.optimization.horizon_hours is None:
logger.error("Optimization horizon unknown - defaulting to 24 hours.")
logger.info("Optimization horizon unknown - defaulting to 24 hours.")
cls.config.optimization.horizon_hours = 24
if cls.config.optimization.interval is None:
logger.error("Optimization interval unknown - defaulting to 3600 seconds.")
logger.info("Optimization interval unknown - defaulting to 3600 seconds.")
cls.config.optimization.interval = 3600
if cls.config.optimization.interval != 3600:
logger.error(
logger.info(
"Optimization interval '{}' seconds not supported - forced to 3600 seconds."
)
cls.config.optimization.interval = 3600
# Check genetic algorithm definitions
if cls.config.optimization.genetic is None:
logger.error(
logger.info(
"Genetic optimization configuration not configured - defaulting to demo config."
)
cls.config.optimization.genetic = {
@@ -215,16 +215,16 @@ class GeneticOptimizationParameters(
},
}
if cls.config.optimization.genetic.individuals is None:
logger.error("Genetic individuals unknown - defaulting to 300.")
logger.info("Genetic individuals unknown - defaulting to 300.")
cls.config.optimization.genetic.individuals = 300
if cls.config.optimization.genetic.generations is None:
logger.error("Genetic generations unknown - defaulting to 400.")
logger.info("Genetic generations unknown - defaulting to 400.")
cls.config.optimization.genetic.generations = 400
if cls.config.optimization.genetic.penalties is None:
logger.error("Genetic penalties unknown - defaulting to demo config.")
logger.info("Genetic penalties unknown - defaulting to demo config.")
cls.config.optimization.genetic.penalties = {"ev_soc_miss": 10}
if "ev_soc_miss" not in cls.config.optimization.genetic.penalties:
logger.error("ev_soc_miss penalty function parameter unknown - defaulting to 100.")
logger.info("ev_soc_miss penalty function parameter unknown - defaulting to 10.")
cls.config.optimization.genetic.penalties["ev_soc_miss"] = 10
# Get start solution from last run
@@ -262,7 +262,7 @@ class GeneticOptimizationParameters(
* power_to_energy_per_interval_factor
).tolist()
except:
logger.exception(
logger.info(
"No PV forecast data available - defaulting to demo data. Parameter preparation attempt {}.",
attempt,
)
@@ -270,6 +270,7 @@ class GeneticOptimizationParameters(
{
"pvforecast": {
"provider": "PVForecastAkkudoktor",
"max_planes": 4,
"planes": [
{
"peakpower": 5.0,
@@ -314,7 +315,7 @@ class GeneticOptimizationParameters(
fill_method="ffill",
).tolist()
except:
logger.exception(
logger.info(
"No Electricity Marketprice forecast data available - defaulting to demo data. Parameter preparation attempt {}.",
attempt,
)
@@ -330,7 +331,7 @@ class GeneticOptimizationParameters(
fill_method="ffill",
).tolist()
except:
logger.exception(
logger.info(
"No Load forecast data available - defaulting to demo data. Parameter preparation attempt {}.",
attempt,
)
@@ -357,7 +358,7 @@ class GeneticOptimizationParameters(
fill_method="ffill",
).tolist()
except:
logger.exception(
logger.info(
"No feed in tariff forecast data available - defaulting to demo data. Parameter preparation attempt {}.",
attempt,
)
@@ -384,7 +385,7 @@ class GeneticOptimizationParameters(
fill_method="ffill",
).tolist()
except:
logger.exception(
logger.info(
"No weather forecast data available - defaulting to demo data. Parameter preparation attempt {}.",
attempt,
)
@@ -397,14 +398,14 @@ class GeneticOptimizationParameters(
# Batteries
# ---------
if cls.config.devices.max_batteries is None:
logger.error("Number of battery devices not configured - defaulting to 1.")
logger.info("Number of battery devices not configured - defaulting to 1.")
cls.config.devices.max_batteries = 1
if cls.config.devices.max_batteries == 0:
battery_params = None
battery_lcos_kwh = 0
else:
if cls.config.devices.batteries is None:
logger.error("No battery device data available - defaulting to demo data.")
logger.info("No battery device data available - defaulting to demo data.")
cls.config.devices.batteries = [{"device_id": "battery1", "capacity_wh": 8000}]
try:
battery_config = cls.config.devices.batteries[0]
@@ -418,7 +419,7 @@ class GeneticOptimizationParameters(
max_soc_percentage=battery_config.max_soc_percentage,
)
except:
logger.exception(
logger.info(
"No battery device data available - defaulting to demo data. Parameter preparation attempt {}.",
attempt,
)
@@ -427,7 +428,7 @@ class GeneticOptimizationParameters(
continue
# Levelized cost of ownership
if battery_config.levelized_cost_of_storage_kwh is None:
logger.error(
logger.info(
"No battery device LCOS data available - defaulting to 0 €/kWh. Parameter preparation attempt {}.",
attempt,
)
@@ -449,7 +450,7 @@ class GeneticOptimizationParameters(
except:
initial_soc_percentage = None
if initial_soc_percentage is None:
logger.error(
logger.info(
f"No battery device SoC data (measurement key = '{battery_config.measurement_key_soc_factor}') available - defaulting to 0."
)
initial_soc_percentage = 0
@@ -458,13 +459,13 @@ class GeneticOptimizationParameters(
# Electric Vehicles
# -----------------
if cls.config.devices.max_electric_vehicles is None:
logger.error("Number of electric_vehicle devices not configured - defaulting to 1.")
logger.info("Number of electric_vehicle devices not configured - defaulting to 1.")
cls.config.devices.max_electric_vehicles = 1
if cls.config.devices.max_electric_vehicles == 0:
electric_vehicle_params = None
else:
if cls.config.devices.electric_vehicles is None:
logger.error(
logger.info(
"No electric vehicle device data available - defaulting to demo data."
)
cls.config.devices.max_electric_vehicles = 1
@@ -489,7 +490,7 @@ class GeneticOptimizationParameters(
max_soc_percentage=electric_vehicle_config.max_soc_percentage,
)
except:
logger.exception(
logger.info(
"No electric_vehicle device data available - defaulting to demo data. Parameter preparation attempt {}.",
attempt,
)
@@ -520,7 +521,7 @@ class GeneticOptimizationParameters(
except:
initial_soc_percentage = None
if initial_soc_percentage is None:
logger.error(
logger.info(
f"No electric vehicle device SoC data (measurement key = '{electric_vehicle_config.measurement_key_soc_factor}') available - defaulting to 0."
)
initial_soc_percentage = 0
@@ -529,13 +530,13 @@ class GeneticOptimizationParameters(
# Inverters
# ---------
if cls.config.devices.max_inverters is None:
logger.error("Number of inverter devices not configured - defaulting to 1.")
logger.info("Number of inverter devices not configured - defaulting to 1.")
cls.config.devices.max_inverters = 1
if cls.config.devices.max_inverters == 0:
inverter_params = None
else:
if cls.config.devices.inverters is None:
logger.error("No inverter device data available - defaulting to demo data.")
logger.info("No inverter device data available - defaulting to demo data.")
cls.config.devices.inverters = [
{
"device_id": "inverter1",
@@ -551,7 +552,7 @@ class GeneticOptimizationParameters(
battery_id=inverter_config.battery_id,
)
except:
logger.exception(
logger.info(
"No inverter device data available - defaulting to demo data. Parameter preparation attempt {}.",
attempt,
)
@@ -568,14 +569,14 @@ class GeneticOptimizationParameters(
# Home Appliances
# ---------------
if cls.config.devices.max_home_appliances is None:
logger.error("Number of home appliance devices not configured - defaulting to 1.")
logger.info("Number of home appliance devices not configured - defaulting to 1.")
cls.config.devices.max_home_appliances = 1
if cls.config.devices.max_home_appliances == 0:
home_appliance_params = None
else:
home_appliance_params = None
if cls.config.devices.home_appliances is None:
logger.error(
logger.info(
"No home appliance device data available - defaulting to demo data."
)
cls.config.devices.home_appliances = [
@@ -606,7 +607,7 @@ class GeneticOptimizationParameters(
time_windows=home_appliance_config.time_windows,
)
except:
logger.exception(
logger.info(
"No home appliance device data available - defaulting to demo data. Parameter preparation attempt {}.",
attempt,
)
@@ -639,7 +640,7 @@ class GeneticOptimizationParameters(
start_solution=start_solution,
)
except:
logger.exception(
logger.info(
"Can not prepare optimization parameters - will retry. Parameter preparation attempt {}.",
attempt,
)