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InconsistentVersionWarning #463

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gieljnssns opened this issue Feb 17, 2025 · 2 comments
Closed

InconsistentVersionWarning #463

gieljnssns opened this issue Feb 17, 2025 · 2 comments

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@gieljnssns
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Describe the bug
I have made the update to v0.12.7 and now I see some InconsistentVersionWarning in the logs

To Reproduce
Update to v0.12.7 and look at the logs

Expected behavior
I don't know if this an error or this can be ignored

Screenshots
If applicable, add screenshots to help explain your problem.

Home Assistant installation type

  • Home Assistant OS

Your hardware

  • OS: HA OS,
  • Architecture: amd64

EMHASS installation type

  • Add-on

Additional context

[2025-02-17 13:25:00 +0100] [27] [INFO]  >> Obtaining params: 
[2025-02-17 13:25:00 +0100] [27] [INFO] Passed runtime parameters: {'prod_price_forecast': [-0.11, -0.11, -0.11, -0.11, -0.11, -0.11, -0.11, -0.11, -0.11, -0.11, -0.11, -0.11, -0.11, -0.11, -0.11, -0.11, -0.11, -0.11, -0.11, -0.11, -0.11, -0.11], 'load_cost_forecast': [0.164497535, 0.164497535, 0.164497535, 0.164497535, 0.164497535, 0.174497535, 0.174497535, 0.174497535, 0.174497535, 0.174497535, 0.174497535, 0.164497535, 0.164497535, 0.164497535, 0.164497535, 0.164497535, 0.164497535, 0.164497535, 0.164497535, 0.164497535, 0.164497535, 0.164497535], 'pv_power_forecast': [5233, 4280, 4163, 4001, 3735, 3104, 2433, 1375, 543, 17, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0], 'prediction_horizon': 22, 'alpha': 1, 'beta': 0, 'num_def_loads': 5, 'p_deferrable_nom': [2000, 2000, 1700, 900, 2000], 'def_total_hours': [0.0, 0.0, 0.0, 2.0, 0.0], 'set_def_constant': [True, True, True, True, True], 'def_start_timestep': [0, 0, 0, 0, 0], 'def_end_timestep': [0, 0, 0, 20, 0], 'def_current_state': [False, False, False, True, False]}
[2025-02-17 13:25:00 +0100] [27] [INFO]  >> Setting input data dict
[2025-02-17 13:25:00 +0100] [27] [INFO] Setting up needed data
[2025-02-17 13:25:00 +0100] [27] [INFO] Retrieve hass get data method initiated...
[2025-02-17 13:25:00 +0100] [27] [INFO] Retrieving weather forecast data using method = list
[2025-02-17 13:25:00 +0100] [27] [INFO] Retrieving data from hass for load forecast using method = mlforecaster
[2025-02-17 13:25:00 +0100] [27] [INFO] Retrieve hass get data method initiated...
/app/.venv/lib/python3.12/site-packages/sklearn/base.py:380: InconsistentVersionWarning:
Trying to unpickle estimator KNeighborsRegressor from version 1.6.0 when using version 1.6.1. This might lead to breaking code or invalid results. Use at your own risk. For more info please refer to:
https://scikit-learn.org/stable/model_persistence.html#security-maintainability-limitations
[2025-02-17 13:25:02 +0100] [27] [DEBUG] Number of ML predict forcast data generated (lags_opt): 48
[2025-02-17 13:25:02 +0100] [27] [DEBUG] Number of forcast dates obtained: 22
[2025-02-17 13:25:02 +0100] [27] [INFO]  >> Performing naive MPC optimization...
[2025-02-17 13:25:02 +0100] [27] [INFO] Performing naive MPC optimization
[2025-02-17 13:25:02 +0100] [27] [INFO] Perform an iteration of a naive MPC controller
[2025-02-17 13:25:02 +0100] [27] [DEBUG] Deferrable load 0: Proposed optimization window: 0 --> 0
[2025-02-17 13:25:02 +0100] [27] [DEBUG] Deferrable load 0: Validated optimization window: 0 --> 0
[2025-02-17 13:25:02 +0100] [27] [DEBUG] Deferrable load 1: Proposed optimization window: 0 --> 0
[2025-02-17 13:25:02 +0100] [27] [DEBUG] Deferrable load 1: Validated optimization window: 0 --> 0
[2025-02-17 13:25:02 +0100] [27] [DEBUG] Deferrable load 2: Proposed optimization window: 0 --> 0
[2025-02-17 13:25:02 +0100] [27] [DEBUG] Deferrable load 2: Validated optimization window: 0 --> 0
[2025-02-17 13:25:02 +0100] [27] [DEBUG] Deferrable load 3: Proposed optimization window: 0 --> 20
[2025-02-17 13:25:02 +0100] [27] [DEBUG] Deferrable load 3: Validated optimization window: 0 --> 20
[2025-02-17 13:25:02 +0100] [27] [DEBUG] Deferrable load 4: Proposed optimization window: 0 --> 0
[2025-02-17 13:25:02 +0100] [27] [DEBUG] Deferrable load 4: Validated optimization window: 0 --> 0
[2025-02-17 13:25:02 +0100] [27] [INFO] Status: Optimal
[2025-02-17 13:25:02 +0100] [27] [INFO] Total value of the Cost function = -2.12
[2025-02-17 13:25:42 +0100] [27] [INFO]  >> Obtaining params: 
[2025-02-17 13:25:42 +0100] [27] [INFO] Passed runtime parameters: {'custom_deferrable_forecast_id': [{'entity_id': 'sensor.emhass_wasmachien', 'unit_of_measurement': 'W', 'friendly_name': 'Emhass wasmachien'}, {'entity_id': 'sensor.emhass_droogkast', 'unit_of_measurement': 'W', 'friendly_name': 'Emhass droogkast'}, {'entity_id': 'sensor.emhass_afwasmachien', 'unit_of_measurement': 'W', 'friendly_name': 'Emhass afwasmachien'}, {'entity_id': 'sensor.emhass_warmtepompboiler', 'unit_of_measurement': 'W', 'friendly_name': 'Emhass warmtepompboiler'}, {'entity_id': 'sensor.emhass_warmtepomp', 'unit_of_measurement': 'W', 'friendly_name': 'Emhass warmtepomp'}], 'custom_pv_forecast_id': {'entity_id': 'sensor.emhass_pv_forecast', 'unit_of_measurement': 'W', 'friendly_name': 'Emhass pv forecast'}, 'custom_load_forecast_id': {'entity_id': 'sensor.emhass_load_forecast', 'unit_of_measurement': 'W', 'friendly_name': 'Emhass load forecast'}, 'custom_grid_forecast_id': {'entity_id': 'sensor.emhass_grid_forecast', 'unit_of_measurement': 'W', 'friendly_name': 'Emhass grid forecast'}, 'custom_unit_load_cost_id': {'entity_id': 'sensor.emhass_load_cost', 'unit_of_measurement': '€/kWh', 'friendly_name': 'Emhass load cost'}, 'custom_unit_prod_price_id': {'entity_id': 'sensor.emhass_prod_price', 'unit_of_measurement': '€/kWh', 'friendly_name': 'Emhass production price'}, 'custom_pv_curtailment_id': {'entity_id': 'sensor.emhass_curtailment', 'unit_of_measurement': 'W', 'friendly_name': 'Emhass curtailment'}, 'publish_prefix': ''}
[2025-02-17 13:25:42 +0100] [27] [INFO]  >> Setting input data dict
[2025-02-17 13:25:42 +0100] [27] [INFO] Setting up needed data
[2025-02-17 13:25:42 +0100] [27] [INFO]  >> Publishing data...
[2025-02-17 13:25:42 +0100] [27] [INFO] Publishing data to HASS instance
[2025-02-17 13:25:42 +0100] [27] [INFO] Successfully posted to sensor.emhass_pv_forecast = 5233
[2025-02-17 13:25:42 +0100] [27] [INFO] Successfully posted to sensor.emhass_load_forecast = 1029.36
[2025-02-17 13:25:42 +0100] [27] [INFO] Successfully posted to sensor.emhass_wasmachien = 0.0
[2025-02-17 13:25:42 +0100] [27] [INFO] Successfully posted to sensor.emhass_droogkast = 0.0
[2025-02-17 13:25:42 +0100] [27] [INFO] Successfully posted to sensor.emhass_afwasmachien = 0.0
[2025-02-17 13:25:42 +0100] [27] [INFO] Successfully posted to sensor.emhass_warmtepompboiler = 900.0
[2025-02-17 13:25:42 +0100] [27] [INFO] Successfully posted to sensor.emhass_warmtepomp = 0.0
[2025-02-17 13:25:42 +0100] [27] [INFO] Successfully posted to sensor.emhass_grid_forecast = -3303.64
[2025-02-17 13:25:42 +0100] [27] [INFO] Successfully posted to sensor.total_cost_fun_value = -2.12
[2025-02-17 13:25:42 +0100] [27] [INFO] Successfully posted to sensor.optim_status = Optimal
[2025-02-17 13:25:42 +0100] [27] [INFO] Successfully posted to sensor.emhass_load_cost = 0.1645
[2025-02-17 13:25:42 +0100] [27] [INFO] Successfully posted to sensor.emhass_prod_price = -0.11
[2025-02-17 13:26:11 +0100] [27] [INFO] EMHASS server online, serving index.html...
[2025-02-17 13:27:01 +0100] [27] [INFO] EMHASS server online, serving index.html...
[2025-02-17 13:30:00 +0100] [27] [INFO]  >> Obtaining params: 
[2025-02-17 13:30:00 +0100] [27] [INFO] Passed runtime parameters: {'prod_price_forecast': [-0.11, -0.11, -0.11, -0.11, -0.11, -0.11, -0.11, -0.11, -0.11, -0.11, -0.11, -0.11, -0.11, -0.11, -0.11, -0.11, -0.11, -0.11, -0.11, -0.11, -0.11, -0.11], 'load_cost_forecast': [0.164497535, 0.164497535, 0.164497535, 0.164497535, 0.164497535, 0.174497535, 0.174497535, 0.174497535, 0.174497535, 0.174497535, 0.174497535, 0.164497535, 0.164497535, 0.164497535, 0.164497535, 0.164497535, 0.164497535, 0.164497535, 0.164497535, 0.164497535, 0.164497535, 0.164497535], 'pv_power_forecast': [4881, 4280, 4163, 4001, 3735, 3104, 2433, 1375, 543, 17, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0], 'prediction_horizon': 22, 'alpha': 1, 'beta': 0, 'num_def_loads': 5, 'p_deferrable_nom': [2000, 2000, 1700, 900, 2000], 'def_total_hours': [0.0, 0.0, 0.0, 2.0, 0.0], 'set_def_constant': [True, True, True, True, True], 'def_start_timestep': [0, 0, 0, 0, 0], 'def_end_timestep': [0, 0, 0, 20, 0], 'def_current_state': [False, False, False, True, False]}
[2025-02-17 13:30:00 +0100] [27] [INFO]  >> Setting input data dict
[2025-02-17 13:30:00 +0100] [27] [INFO] Setting up needed data
[2025-02-17 13:30:00 +0100] [27] [INFO] Retrieve hass get data method initiated...
[2025-02-17 13:30:00 +0100] [27] [INFO] Retrieving weather forecast data using method = list
[2025-02-17 13:30:00 +0100] [27] [INFO] Retrieving data from hass for load forecast using method = mlforecaster
[2025-02-17 13:30:00 +0100] [27] [INFO] Retrieve hass get data method initiated...
/app/.venv/lib/python3.12/site-packages/sklearn/base.py:380: InconsistentVersionWarning:
Trying to unpickle estimator KNeighborsRegressor from version 1.6.0 when using version 1.6.1. This might lead to breaking code or invalid results. Use at your own risk. For more info please refer to:
https://scikit-learn.org/stable/model_persistence.html#security-maintainability-limitations
[2025-02-17 13:30:02 +0100] [27] [DEBUG] Number of ML predict forcast data generated (lags_opt): 48
@davidusb-geek
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Just try to re-train your ML models

@gieljnssns
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A refit of my model has solved this. Thanks

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@gieljnssns @davidusb-geek