I have deferable loads set to 0
My power_no_var_loads is my consumption sensor.
Ive tried piecing it together but it still has no value close together,
What do the logs say?
Are you using daily or mpc optimisation?
By the looks its mpc naive, Im not sure if this influences. also my logs are the same as displayed data. If your talking about the logs within Emhass add on.
shell_command:
dayahead_optim: 'curl -i -H "Content-Type: application/json" -X POST -d ''{}'' http://localhost:5000/action/dayahead-optim'
publish_data: 'curl -i -H "Content-Type: application/json" -X POST -d ''{}'' http://localhost:5000/action/publish-data '
rest_command:
naive_mpc_optim:
url: http://localhost:5000/action/naive-mpc-optim
method: POST
content_type: "application/json"
payload: >-
{
"prod_price_forecast": {{
([states('sensor.home_feed_in_price')|float(0)] +
(state_attr('sensor.home_feed_in_forecast', 'forecasts')|map(attribute='per_kwh')|list))
| tojson
}},
"load_cost_forecast": {{
([states('sensor.home_general_price')|float(0)] +
state_attr('sensor.home_general_forecast', 'forecasts') |map(attribute='per_kwh')|list)
| tojson
}},
"pv_power_forecast": {{
([states('sensor.solar_total')|int(0)] +
state_attr('sensor.solcast_pv_forecast_forecast_today', 'detailedForecast')|selectattr('period_start','gt',utcnow()) | map(attribute='pv_estimate')|map('multiply',1000)|map('int')|list +
state_attr('sensor.solcast_pv_forecast_forecast_tomorrow', 'detailedForecast')|selectattr('period_start','gt',utcnow()) | map(attribute='pv_estimate')|map('multiply',1000)|map('int')|list
)| tojson
}},
"prediction_horizon": {{
min(48, (state_attr('sensor.home_feed_in_forecast', 'forecasts')|map(attribute='per_kwh')|list|length)+1)
}},
"soc_init": {{(states('sensor.battery_total_2')|int(0))/400}},
"soc_final":0.2
}
Try and include the following variables with your MPC call.:
"alpha": 1,
"beta": 0,
https://emhass.readthedocs.io/en/latest/forecasts.html#now-current-values-in-forecasts
Could i ask were i would be putting it?
I tried and it broke the sensor and battery data deleted.
Im not sure exaclty were it should be placed
Anywhere in the payload is fine;
Just note there is no , in the last element of the payload.
naive_mpc_optim:
url: http://localhost:5000/action/naive-mpc-optim
method: POST
content_type: "application/json"
payload: >-
{
"prod_price_forecast": {{
([states('sensor.amber_feed_in_price')|float(0)] +
(state_attr('sensor.amber_feed_in_forecast', 'forecasts')|map(attribute='per_kwh')|list))
| tojson
}},
"load_cost_forecast": {{
([states('sensor.amber_general_price')|float(0)] +
state_attr('sensor.amber_general_forecast', 'forecasts') |map(attribute='per_kwh')|list)
| tojson
}},
"load_power_forecast": {{
([states('sensor.power_load_no_var_loads')|int] +
(states('input_text.fi_fo_buffer').split(', ')|map('multiply',1000)|map('int')|list)[1:]
)| tojson
}},
"prediction_horizon": {{
min(48, (state_attr('sensor.amber_feed_in_forecast', 'forecasts')|map(attribute='per_kwh')|list|length)+1)
}},
"alpha": 1,
"beta": 0,
"num_def_loads": 6,
"def_total_hours": {{[states('sensor.def_total_hours_pool_filter')|int(0),
states('sensor.def_total_hours_pool_heatpump')|int(0),
states('sensor.def_total_hours_ev')|int(0),
states('sensor.def_total_hours_hvac')|int(0),
states('sensor.def_total_hours_hws')|int(0),
states('sensor.def_total_hours_ev2')|int(0)]}},
"def_end_timestep":[0, 0, 0, 0, 0, 0],
"P_deferrable_nom": [300,
6333,
{{ states('sensor.p_nom_ev')}},
{{ states('input_number.p_nom_hvac')}},
600,
{{ states('sensor.p_nom_ev2')}}],
"treat_def_as_semi_cont": [1, 1, 0, 0, 1, 0],
"set_def_constant": [0, 0, 0, 0, 0, 0],
"def_start_penalty": [1, 1, 1, 1, 1, 1],
"soc_init": {{ max(0,states('sensor.energy_site_percentage_charged')|int(0))/100 }},
"soc_final": {{ max(1,states('sensor.gateway_battery')|int(0)/100) }}
}
I tried this and it doesnt calculate
The battery goes to 0
shell_command:
dayahead_optim: 'curl -i -H "Content-Type: application/json" -X POST -d ''{}'' http://localhost:5000/action/dayahead-optim'
publish_data: 'curl -i -H "Content-Type: application/json" -X POST -d ''{}'' http://localhost:5000/action/publish-data '
rest_command:
naive_mpc_optim:
url: http://localhost:5000/action/naive-mpc-optim
method: POST
content_type: "application/json"
payload: >-
{
"prod_price_forecast": {{
([states('sensor.home_feed_in_price')|float(0)] +
(state_attr('sensor.home_feed_in_forecast', 'forecasts')|map(attribute='per_kwh')|list))
| tojson
}},
"load_cost_forecast": {{
([states('sensor.home_general_price')|float(0)] +
state_attr('sensor.home_general_forecast', 'forecasts') |map(attribute='per_kwh')|list)
| tojson
}},
"pv_power_forecast": {{
([states('sensor.solar_total')|int(0)] +
state_attr('sensor.solcast_pv_forecast_forecast_today', 'detailedForecast')|selectattr('period_start','gt',utcnow()) | map(attribute='pv_estimate')|map('multiply',1000)|map('int')|list +
state_attr('sensor.solcast_pv_forecast_forecast_tomorrow', 'detailedForecast')|selectattr('period_start','gt',utcnow()) | map(attribute='pv_estimate')|map('multiply',1000)|map('int')|list
)| tojson
}},
"prediction_horizon": {{
min(48, (state_attr('sensor.home_feed_in_forecast', 'forecasts')|map(attribute='per_kwh')|list|length)+1)
}},
"soc_init": {{(states('sensor.battery_total_2')|int(0))/400}},
"soc_final":0.2
"alpha": 1,
"beta": 0,
}
You need to move your commas around.
The last item on the list doesnāt have a comma and you need to add one to soc_final:
soc_final":0.2,
"alpha": 1,
"beta": 0
}
Yep nailed it,
The code worked but its still similar results. I cant see why as im feeding the excact sensor into emhass.
Could you share your EMHASS logs that show the input and output please?
You can see from my logs that my PV and load sensors exactly match my inputs.
2024-09-03 06:31:00,377 - web_server - INFO - Passed runtime parameters: {'load_cost_forecast': [0.16, 0.12, 0.09, 0.07, 0.07, 0.04, 0.04, 0.04, 0.03, 0.02, 0.03, 0.04, 0.04, 0.04, 0.04, 0.04, 0.05, 0.06, 0.08, 0.26, 0.29, 0.34, 0.4, 0.44, 0.43, 0.41, 0.39, 0.38, 0.36, 0.23, 0.22, 0.21, 0.21, 0.21, 0.2, 0.2, 0.2, 0.19, 0.19, 0.19, 0.19, 0.19, 0.19], 'prod_price_forecast': [0.04, 0, -0.02, -0.04, -0.04, -0.04, -0.04, -0.05, -0.05, -0.06, -0.05, -0.05, -0.05, -0.05, -0.05, -0.04, -0.04, -0.03, -0.01, 0.01, 0.04, 0.09, 0.15, 0.18, 0.17, 0.15, 0.13, 0.13, 0.11, 0.1, 0.09, 0.09, 0.09, 0.08, 0.08, 0.08, 0.08, 0.07, 0.07, 0.07, 0.07, 0.07, 0.07], 'load_power_forecast': [400, 300, 300, 400, 400, 600, 500, 300, 300, 300, 300, 300, 300, 300, 300, 300, 400, 300, 300, 300, 300, 400, 400, 400, 400, 300, 300, 300, 300, 300, 300, 300, 300, 300, 300, 300, 300, 300, 300, 300, 300, 300, 300, 300, 300, 300, 500, 300, 400, 300, 300, 400, 400, 600, 500, 300, 300, 300, 300, 300, 300, 300, 300, 300, 400, 300, 300, 300, 300, 400, 400, 400, 400, 300, 300, 300, 300, 300, 300, 300, 300, 300, 300, 300, 300, 300, 300, 300, 300, 300, 300, 300, 300, 300, 500, 300], 'pv_power_forecast': [372, 2114, 3797, 5456, 7053, 8526, 9773, 10796, 11623, 12178, 12497, 12569, 12404, 12013, 11357, 10505, 9376, 8002, 6411, 4655, 2746, 839, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 115, 647, 1996, 3250, 4499, 5687, 6758, 7623, 8316, 8818, 9123, 9242, 9269, 9177, 8890, 8474, 7552, 6164, 4951, 3734, 2273, 723, 145, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 165, 893, 2145, 3510, 4828, 6009, 7022, 7919, 8724, 9360, 9794, 10071, 10184, 10033, 9753, 9439, 8841, 7875, 6564, 5106, 3565, 1766, 306, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0], 'prediction_horizon': 43, 'alpha': 1, 'beta': 0, 'num_def_loads': 6, 'def_total_hours': [8, 0, 0, 4, 0, 0], 'def_end_timestep': [0, 0, 0, 0, 0, 0], 'P_deferrable_nom': [300, 6333, 11520, 9000, 600, 11520], 'def_current_state': [0, 0, 0, 0, 0, 0], 'def_start_penalty': [1, 1, 1, 1, 1, 1], 'treat_def_as_semi_cont': [1, 1, 0, 0, 1, 0], 'set_def_constant': [0, 0, 0, 0, 0, 0], 'soc_init': 0.0, 'soc_final': 1}
2024-09-03 06:31:00,378 - web_server - INFO - >> Setting input data dict
2024-09-03 06:31:00,378 - web_server - INFO - Setting up needed data
2024-09-03 06:31:00,384 - web_server - INFO - Retrieve hass get data method initiated...
2024-09-03 06:31:00,914 - web_server - INFO - Retrieving weather forecast data using method = list
2024-09-03 06:31:00,923 - web_server - INFO - >> Performing naive MPC optimization...
2024-09-03 06:31:00,923 - web_server - INFO - Performing naive MPC optimization
2024-09-03 06:31:00,956 - web_server - INFO - Perform an iteration of a naive MPC controller
2024-09-03 06:31:01,172 - web_server - DEBUG - Deferrable load 0: Proposed optimization window: 0 --> 0
2024-09-03 06:31:01,172 - web_server - DEBUG - Deferrable load 0: Validated optimization window: 0 --> 0
2024-09-03 06:31:01,181 - web_server - DEBUG - Deferrable load 1: Proposed optimization window: 0 --> 0
2024-09-03 06:31:01,181 - web_server - DEBUG - Deferrable load 1: Validated optimization window: 0 --> 0
2024-09-03 06:31:01,190 - web_server - DEBUG - Deferrable load 2: Proposed optimization window: 0 --> 0
2024-09-03 06:31:01,190 - web_server - DEBUG - Deferrable load 2: Validated optimization window: 0 --> 0
2024-09-03 06:31:01,196 - web_server - DEBUG - Deferrable load 3: Proposed optimization window: 0 --> 0
2024-09-03 06:31:01,196 - web_server - DEBUG - Deferrable load 3: Validated optimization window: 0 --> 0
2024-09-03 06:31:01,201 - web_server - DEBUG - Deferrable load 4: Proposed optimization window: 0 --> 0
2024-09-03 06:31:01,202 - web_server - DEBUG - Deferrable load 4: Validated optimization window: 0 --> 0
2024-09-03 06:31:01,213 - web_server - DEBUG - Deferrable load 5: Proposed optimization window: 0 --> 0
2024-09-03 06:31:01,213 - web_server - DEBUG - Deferrable load 5: Validated optimization window: 0 --> 0
2024-09-03 06:31:02,171 - web_server - INFO - Status: Optimal
2024-09-03 06:31:02,172 - web_server - INFO - Total value of the Cost function = -0.67
2024-09-03 06:31:03,218 - web_server - INFO - Passed runtime parameters: {'custom_unit_load_cost_id': {'entity_id': 'sensor.unit_load_cost', 'unit_of_measurement': '$/kWh', 'friendly_name': 'Load Cost'}, 'custom_unit_prod_price_id': {'entity_id': 'sensor.unit_prod_price', 'unit_of_measurement': '$/kWh', 'friendly_name': 'Prod Price'}}
2024-09-03 06:31:03,218 - web_server - INFO - >> Setting input data dict
2024-09-03 06:31:03,218 - web_server - INFO - Setting up needed data
2024-09-03 06:31:03,223 - web_server - INFO - >> Publishing data...
2024-09-03 06:31:03,223 - web_server - INFO - Publishing data to HASS instance
2024-09-03 06:31:03,256 - web_server - INFO - Successfully posted to sensor.p_pv_forecast = 372
2024-09-03 06:31:03,278 - web_server - INFO - Successfully posted to sensor.p_load_forecast = 400
2024-09-03 06:31:03,299 - web_server - INFO - Successfully posted to sensor.p_pv_curtailment = 0.0
2024-09-03 06:31:03,320 - web_server - INFO - Successfully posted to sensor.p_deferrable0 = 0.0
2024-09-03 06:31:03,340 - web_server - INFO - Successfully posted to sensor.p_deferrable1 = 0.0
2024-09-03 06:31:03,361 - web_server - INFO - Successfully posted to sensor.p_deferrable2 = 0.0
2024-09-03 06:31:03,382 - web_server - INFO - Successfully posted to sensor.p_deferrable3 = 0.0
2024-09-03 06:31:03,402 - web_server - INFO - Successfully posted to sensor.p_deferrable4 = 0.0
2024-09-03 06:31:03,423 - web_server - INFO - Successfully posted to sensor.p_deferrable5 = 0.0
2024-09-03 06:31:03,443 - web_server - INFO - Successfully posted to sensor.p_batt_forecast = 0.0
2024-09-03 06:31:03,467 - web_server - INFO - Successfully posted to sensor.soc_batt_forecast = 0.0
2024-09-03 06:31:03,488 - web_server - INFO - Successfully posted to sensor.p_grid_forecast = 28.0
2024-09-03 06:31:03,505 - web_server - INFO - Successfully posted to sensor.total_cost_fun_value = -0.57
2024-09-03 06:31:03,520 - web_server - INFO - Successfully posted to sensor.optim_status = Optimal
2024-09-03 06:31:03,541 - web_server - INFO - Successfully posted to sensor.unit_load_cost = 0.16
2024-09-03 06:31:03,562 - web_server - INFO - Successfully posted to sensor.unit_prod_price = 0.04
2024-09-03 16:32:46,663 - web_server - INFO - >> Publishing dataā¦
2024-09-03 16:32:46,663 - web_server - INFO - Publishing data to HASS instance
2024-09-03 16:32:46,677 - web_server - INFO - Successfully posted to sensor.p_pv_forecast = 2624.68
2024-09-03 16:32:46,690 - web_server - INFO - Successfully posted to sensor.p_load_forecast = 961.7
2024-09-03 16:32:46,701 - web_server - INFO - Successfully posted to sensor.p_pv_curtailment = 0.0
2024-09-03 16:32:46,711 - web_server - INFO - Successfully posted to sensor.p_deferrable0 = 0.0
2024-09-03 16:32:46,720 - web_server - INFO - Successfully posted to sensor.p_batt_forecast = -460.0
2024-09-03 16:32:46,729 - web_server - INFO - Successfully posted to sensor.soc_batt_forecast = 100.0
2024-09-03 16:32:46,740 - web_server - INFO - Successfully posted to sensor.p_grid_forecast = -1202.97
2024-09-03 16:32:46,748 - web_server - INFO - Successfully posted to sensor.total_cost_fun_value = 7.98
2024-09-03 16:32:46,755 - web_server - INFO - Successfully posted to sensor.optim_status = Optimal
2024-09-03 16:32:46,764 - web_server - INFO - Successfully posted to sensor.unit_load_cost = 0.13
2024-09-03 16:32:46,773 - web_server - INFO - Successfully posted to sensor.unit_prod_price = 0.08
2024-09-03 16:32:50,425 - web_server - INFO - Passed runtime parameters: {āprod_price_forecastā: [0.08, 0.09, 0.34, 0.34, 0.34, 0.33, 0.33, 0.21, 0.32, 0.14, 0.11, 0.09, 0.08, 0.08, 0.08, 0.08, 0.07, 0.06, 0.06, 0.06, 0.06, 0.06, 0.06, 0.06, 0.06, 0.06, 0.08, 0.09, 0.09, 0.08, 0.07, 0.07, 0.04, 0.02, -0.01, -0.06, -0.06, -0.07, -0.07, -0.08, -0.08, -0.08, -0.08, -0.07, -0.06, -0.05, -0.06, -0.03, -0.02], āload_cost_forecastā: [0.13, 0.15, 0.42, 0.42, 0.42, 0.41, 0.41, 0.28, 0.39, 0.23, 0.19, 0.17, 0.16, 0.16, 0.16, 0.16, 0.15, 0.14, 0.14, 0.14, 0.14, 0.14, 0.14, 0.14, 0.14, 0.14, 0.16, 0.17, 0.17, 0.16, 0.15, 0.15, 0.11, 0.09, 0.06, 0.02, 0.02, 0.01, 0.01, -0.0, -0.0, -0.0, -0.0, 0.01, 0.02, 0.02, 0.01, 0.02, 0.02], āpv_power_forecastā: [2952, 1234, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 64, 661, 1724, 2779, 3966, 5806, 7524, 8939, 10218, 11224, 11969, 12478, 12751, 12757, 12401, 11880, 11055, 9956, 8365, 6629, 4916, 2846, 900, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0], āprediction_horizonā: 48, āsoc_initā: 0.995, āsoc_finalā: 0.2}
2024-09-03 16:32:50,426 - web_server - INFO - >> Setting input data dict
2024-09-03 16:32:50,426 - web_server - INFO - Setting up needed data
2024-09-03 16:32:50,429 - web_server - INFO - Retrieve hass get data method initiatedā¦
2024-09-03 16:32:52,025 - web_server - INFO - Retrieving weather forecast data using method = list
2024-09-03 16:32:52,026 - web_server - INFO - Retrieving data from hass for load forecast using method = naive
2024-09-03 16:32:52,027 - web_server - INFO - Retrieve hass get data method initiated.
I canāt see you setting alpha and beta in this call.
Do you restart home assistant after you made this changes?
2024-09-04 18:01:27,619 - web_server - INFO - Successfully posted to sensor.p_load_forecast = 1006.93
2024-09-04 18:01:27,630 - web_server - INFO - Successfully posted to sensor.p_pv_curtailment = 0.0
2024-09-04 18:01:27,641 - web_server - INFO - Successfully posted to sensor.p_deferrable0 = 0.0
2024-09-04 18:01:27,652 - web_server - INFO - Successfully posted to sensor.p_batt_forecast = 10006.93
2024-09-04 18:01:27,666 - web_server - INFO - Successfully posted to sensor.soc_batt_forecast = 68.62
2024-09-04 18:01:27,683 - web_server - INFO - Successfully posted to sensor.p_grid_forecast = -9000.0
2024-09-04 18:01:27,697 - web_server - INFO - Successfully posted to sensor.total_cost_fun_value = 3.63
2024-09-04 18:01:27,710 - web_server - INFO - Successfully posted to sensor.optim_status = Optimal
2024-09-04 18:01:27,722 - web_server - INFO - Successfully posted to sensor.unit_load_cost = 0.23
2024-09-04 18:01:27,735 - web_server - INFO - Successfully posted to sensor.unit_prod_price = 0.16
2024-09-04 18:01:30,229 - web_server - INFO - Passed runtime parameters: {āprod_price_forecastā: [0.16, 0.16, 0.14, 0.12, 0.12, 0.1, 0.07, 0.07, 0.08, 0.08, 0.06, 0.06, 0.06, 0.06, 0.06, 0.06, 0.06, 0.05, 0.05, 0.06, 0.06, 0.06, 0.06, 0.06, 0.07, 0.07, 0.01, 0.03, 0.04, 0.01, -0.0, -0.03, -0.06, -0.06, -0.07, -0.07, -0.07, -0.07, -0.07, -0.06, -0.06, -0.05, -0.03, 0.0, 0.02, 0.02, 0.07, 0.1, 0.12], āload_cost_forecastā: [0.23, 0.22, 0.2, 0.18, 0.17, 0.16, 0.15, 0.15, 0.16, 0.16, 0.14, 0.14, 0.14, 0.14, 0.14, 0.14, 0.14, 0.13, 0.13, 0.14, 0.14, 0.14, 0.14, 0.14, 0.15, 0.15, 0.08, 0.11, 0.11, 0.08, 0.07, 0.04, 0.02, 0.02, 0.01, 0.01, 0.01, 0.01, 0.01, 0.01, 0.02, 0.03, 0.04, 0.07, 0.07, 0.07, 0.12, 0.16, 0.17], āpv_power_forecastā: [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 80, 707, 1772, 2805, 4082, 5783, 7396, 8919, 10152, 11064, 11745, 12184, 12481, 12404, 12180, 11646, 10887, 9866, 8427, 6747, 5381, 3474, 1463, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0], āprediction_horizonā: 48, āsoc_initā: 0.795, āsoc_finalā: 0.2, āalphaā: 1, ābetaā: 0}
2024-09-04 18:01:30,229 - web_server - INFO - >> Setting input data dict
2024-09-04 18:01:30,230 - web_server - INFO - Setting up needed data
2024-09-04 18:01:30,232 - web_server - INFO - Retrieve hass get data method initiatedā¦
2024-09-04 18:01:31,804 - web_server - INFO - Retrieving weather forecast data using method = list
2024-09-04 18:01:31,805 - web_server - INFO - Retrieving data from hass for load forecast using method = naive
2024-09-04 18:01:31,806 - web_server - INFO - Retrieve hass get data method initiatedā¦
2024-09-04 18:01:35,433 - web_server - INFO - >> Performing naive MPC optimizationā¦
2024-09-04 18:01:35,433 - web_server - INFO - Performing naive MPC optimization
2024-09-04 18:01:35,453 - web_server - INFO - Perform an iteration of a naive MPC controller
2024-09-04 18:01:35,667 - web_server - INFO - Status: Optimal
2024-09-04 18:01:35,667 - web_server - INFO - Total value of the Cost function = -23.74
2024-09-04 18:01:36,536 - web_server - INFO - Passed runtime parameters: {}
2024-09-04 18:01:36,536 - web_server - INFO - >> Setting input data dict
2024-09-04 18:01:36,536 - web_server - INFO - Setting up needed data
2024-09-04 18:01:36,538 - web_server - INFO - >> Publishing dataā¦
2024-09-04 18:01:36,539 - web_server - INFO - Publishing data to HASS instance
2024-09-04 18:01:36,552 - web_server - INFO - Successfully posted to sensor.p_pv_forecast = 0
2024-09-04 18:01:36,562 - web_server - INFO - Successfully posted to sensor.p_load_forecast = 1006.93
2024-09-04 18:01:36,572 - web_server - INFO - Successfully posted to sensor.p_pv_curtailment = 0.0
2024-09-04 18:01:36,581 - web_server - INFO - Successfully posted to sensor.p_deferrable0 = 0.0
2024-09-04 18:01:36,590 - web_server - INFO - Successfully posted to sensor.p_batt_forecast = 10006.93
2024-09-04 18:01:36,599 - web_server - INFO - Successfully posted to sensor.soc_batt_forecast = 68.62
2024-09-04 18:01:36,610 - web_server - INFO - Successfully posted to sensor.p_grid_forecast = -9000.0
2024-09-04 18:01:36,618 - web_server - INFO - Successfully posted to sensor.total_cost_fun_value = 3.63
2024-09-04 18:01:36,624 - web_server - INFO - Successfully posted to sensor.optim_status = Optimal
2024-09-04 18:01:36,633 - web_server - INFO - Successfully posted to sensor.unit_load_cost = 0.23
2024-09-04 18:01:36,642 - web_server - INFO - Successfully posted to sensor.unit_prod_price = 0.16
2024-09-04 18:01:40,225 - web_server - INFO - Passed runtime parameters: {āprod_price_forecastā: [0.16, 0.16, 0.14, 0.12, 0.12, 0.1, 0.07, 0.07, 0.08, 0.08, 0.06, 0.06, 0.06, 0.06, 0.06, 0.06, 0.06, 0.05, 0.05, 0.06, 0.06, 0.06, 0.06, 0.06, 0.07, 0.07, 0.01, 0.03, 0.04, 0.01, -0.0, -0.03, -0.06, -0.06, -0.07, -0.07, -0.07, -0.07, -0.07, -0.06, -0.06, -0.05, -0.03, 0.0, 0.02, 0.02, 0.07, 0.1, 0.12], āload_cost_forecastā: [0.23, 0.22, 0.2, 0.18, 0.17, 0.16, 0.15, 0.15, 0.16, 0.16, 0.14, 0.14, 0.14, 0.14, 0.14, 0.14, 0.14, 0.13, 0.13, 0.14, 0.14, 0.14, 0.14, 0.14, 0.15, 0.15, 0.08, 0.11, 0.11, 0.08, 0.07, 0.04, 0.02, 0.02, 0.01, 0.01, 0.01, 0.01, 0.01, 0.01, 0.02, 0.03, 0.04, 0.07, 0.07, 0.07, 0.12, 0.16, 0.17], āpv_power_forecastā: [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 80, 707, 1772, 2805, 4082, 5783, 7396, 8919, 10152, 11064, 11745, 12184, 12481, 12404, 12180, 11646, 10887, 9866, 8427, 6747, 5381, 3474, 1463, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0], āprediction_horizonā: 48, āsoc_initā: 0.795, āsoc_finalā: 0.2, āalphaā: 1, ābetaā: 0}
2024-09-04 18:01:40,225 - web_server - INFO - >> Setting input data dict
2024-09-04 18:01:40,225 - web_server - INFO - Setting up needed data
2024-09-04 18:01:40,228 - web_server - INFO - Retrieve hass get data method initiatedā¦
2024-09-04 18:01:42,102 - web_server - INFO - Retrieving weather forecast data using method = list
2024-09-04 18:01:42,103 - web_server - INFO - Retrieving data from hass for load forecast using method = naive
2024-09-04 18:01:42,104 - web_server - INFO - Retrieve hass get data method initiatedā¦
2024-09-04 18:01:45,623 - web_server - INFO - >> Performing naive MPC optimizationā¦
2024-09-04 18:01:45,623 - web_server - INFO - Performing naive MPC optimization
2024-09-04 18:01:45,637 - web_server - INFO - Perform an iteration of a naive MPC controller
2024-09-04 18:01:45,851 - web_server - INFO - Status: Optimal
2024-09-04 18:01:45,851 - web_server - INFO - Total value of the Cost function = -23.74
2024-09-04 18:01:46,737 - web_server - INFO - Passed runtime parameters: {}
2024-09-04 18:01:46,737 - web_server - INFO - >> Setting input data dict
2024-09-04 18:01:46,737 - web_server - INFO - Setting up needed data
2024-09-04 18:01:46,739 - web_server - INFO - >> Publishing dataā¦
2024-09-04 18:01:46,739 - web_server - INFO - Publishing data to HASS instance
2024-09-04 18:01:46,753 - web_server - INFO - Successfully posted to sensor.p_pv_forecast = 0
2024-09-04 18:01:46,763 - web_server - INFO - Successfully posted to sensor.p_load_forecast = 1006.93
2024-09-04 18:01:46,772 - web_server - INFO - Successfully posted to sensor.p_pv_curtailment = 0.0
2024-09-04 18:01:46,781 - web_server - INFO - Successfully posted to sensor.p_deferrable0 = 0.0
2024-09-04 18:01:46,789 - web_server - INFO - Successfully posted to sensor.p_batt_forecast = 10006.93
2024-09-04 18:01:46,798 - web_server - INFO - Successfully posted to sensor.soc_batt_forecast = 68.62
2024-09-04 18:01:46,808 - web_server - INFO - Successfully posted to sensor.p_grid_forecast = -9000.0
2024-09-04 18:01:46,833 - web_server - INFO - Successfully posted to sensor.total_cost_fun_value = 3.63
2024-09-04 18:01:46,842 - web_server - INFO - Successfully posted to sensor.optim_status = Optimal
2024-09-04 18:01:46,852 - web_server - INFO - Successfully posted to sensor.unit_load_cost = 0.23
2024-09-04 18:01:46,862 - web_server - INFO - Successfully posted to sensor.unit_prod_price = 0.16
2024-09-04 18:01:50,230 - web_server - INFO - Passed runtime parameters: {āprod_price_forecastā: [0.16, 0.16, 0.14, 0.12, 0.12, 0.1, 0.07, 0.07, 0.08, 0.08, 0.06, 0.06, 0.06, 0.06, 0.06, 0.06, 0.06, 0.05, 0.05, 0.06, 0.06, 0.06, 0.06, 0.06, 0.07, 0.07, 0.01, 0.03, 0.04, 0.01, -0.0, -0.03, -0.06, -0.06, -0.07, -0.07, -0.07, -0.07, -0.07, -0.06, -0.06, -0.05, -0.03, 0.0, 0.02, 0.02, 0.07, 0.1, 0.12], āload_cost_forecastā: [0.22, 0.23, 0.2, 0.18, 0.17, 0.16, 0.15, 0.15, 0.16, 0.16, 0.14, 0.14, 0.14, 0.14, 0.14, 0.14, 0.14, 0.13, 0.13, 0.14, 0.14, 0.14, 0.14, 0.14, 0.15, 0.15, 0.08, 0.11, 0.11, 0.08, 0.07, 0.04, 0.02, 0.02, 0.01, 0.01, 0.01, 0.01, 0.01, 0.01, 0.02, 0.03, 0.04, 0.07, 0.07, 0.07, 0.12, 0.16, 0.17], āpv_power_forecastā: [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 80, 707, 1772, 2805, 4082, 5783, 7396, 8919, 10152, 11064, 11745, 12184, 12481, 12404, 12180, 11646, 10887, 9866, 8427, 6747, 5381, 3474, 1463, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0], āprediction_horizonā: 48, āsoc_initā: 0.795, āsoc_finalā: 0.2, āalphaā: 1, ābetaā: 0}
2024-09-04 18:01:50,231 - web_server - INFO - >> Setting input data dict
2024-09-04 18:01:50,231 - web_server - INFO - Setting up needed data
2024-09-04 18:01:50,234 - web_server - INFO - Retrieve hass get data method initiatedā¦
2024-09-04 18:01:51,831 - web_server - INFO - Retrieving weather forecast data using method = list
2024-09-04 18:01:51,833 - web_server - INFO - Retrieving data from hass for load forecast using method = naive
2024-09-04 18:01:51,839 - web_server - INFO - Retrieve hass get data method initiatedā¦
2024-09-04 18:01:55,290 - web_server - INFO - >> Performing naive MPC optimizationā¦
2024-09-04 18:01:55,290 - web_server - INFO - Performing naive MPC optimization
2024-09-04 18:01:55,304 - web_server - INFO - Perform an iteration of a naive MPC controller
2024-09-04 18:01:55,518 - web_server - INFO - Status: Optimal
2024-09-04 18:01:55,519 - web_server - INFO - Total value of the Cost function = -23.74
2024-09-04 18:01:56,400 - web_server - INFO - Passed runtime parameters: {}
2024-09-04 18:01:56,400 - web_server - INFO - >> Setting input data dict
2024-09-04 18:01:56,400 - web_server - INFO - Setting up needed data
2024-09-04 18:01:56,402 - web_server - INFO - >> Publishing dataā¦
2024-09-04 18:01:56,402 - web_server - INFO - Publishing data to HASS instance
2024-09-04 18:01:56,415 - web_server - INFO - Successfully posted to sensor.p_pv_forecast = 0
2024-09-04 18:01:56,426 - web_server - INFO - Successfully posted to sensor.p_load_forecast = 1006.93
2024-09-04 18:01:56,436 - web_server - INFO - Successfully posted to sensor.p_pv_curtailment = 0.0
2024-09-04 18:01:56,445 - web_server - INFO - Successfully posted to sensor.p_deferrable0 = 0.0
2024-09-04 18:01:56,454 - web_server - INFO - Successfully posted to sensor.p_batt_forecast = 10006.93
2024-09-04 18:01:56,463 - web_server - INFO - Successfully posted to sensor.soc_batt_forecast = 68.62
2024-09-04 18:01:56,474 - web_server - INFO - Successfully posted to sensor.p_grid_forecast = -9000.0
2024-09-04 18:01:56,483 - web_server - INFO - Successfully posted to sensor.total_cost_fun_value = 3.63
2024-09-04 18:01:56,490 - web_server - INFO - Successfully posted to sensor.optim_status = Optimal
2024-09-04 18:01:56,500 - web_server - INFO - Successfully posted to sensor.unit_load_cost = 0.22
2024-09-04 18:01:56,510 - web_server - INFO - Successfully posted to sensor.unit_prod_price = 0.16
2024-09-04 18:02:00,271 - web_server - INFO - Passed runtime parameters: {āprod_price_forecastā: [0.16, 0.16, 0.14, 0.12, 0.12, 0.1, 0.07, 0.07, 0.08, 0.08, 0.06, 0.06, 0.06, 0.06, 0.06, 0.06, 0.06, 0.05, 0.05, 0.06, 0.06, 0.06, 0.06, 0.06, 0.07, 0.07, 0.01, 0.03, 0.04, 0.01, -0.0, -0.03, -0.06, -0.06, -0.07, -0.07, -0.07, -0.07, -0.07, -0.06, -0.06, -0.05, -0.03, 0.0, 0.02, 0.02, 0.07, 0.1, 0.12], āload_cost_forecastā: [0.22, 0.23, 0.2, 0.18, 0.17, 0.16, 0.15, 0.15, 0.16, 0.16, 0.14, 0.14, 0.14, 0.14, 0.14, 0.14, 0.14, 0.13, 0.13, 0.14, 0.14, 0.14, 0.14, 0.14, 0.15, 0.15, 0.08, 0.11, 0.11, 0.08, 0.07, 0.04, 0.02, 0.02, 0.01, 0.01, 0.01, 0.01, 0.01, 0.01, 0.02, 0.03, 0.04, 0.07, 0.07, 0.07, 0.12, 0.16, 0.17], āpv_power_forecastā: [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 80, 707, 1772, 2805, 4082, 5783, 7396, 8919, 10152, 11064, 11745, 12184, 12481, 12404, 12180, 11646, 10887, 9866, 8427, 6747, 5381, 3474, 1463, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0], āprediction_horizonā: 48, āsoc_initā: 0.795, āsoc_finalā: 0.2, āalphaā: 1, ābetaā: 0}
2024-09-04 18:02:00,271 - web_server - INFO - >> Setting input data dict
2024-09-04 18:02:00,271 - web_server - INFO - Setting up needed data
2024-09-04 18:02:00,275 - web_server - INFO - Retrieve hass get data method initiatedā¦
2024-09-04 18:02:02,287 - web_server - INFO - Retrieving weather forecast data using method = list
2024-09-04 18:02:02,288 - web_server - INFO - Retrieving data from hass for load forecast using method = naive
2024-09-04 18:02:02,288 - web_server - INFO - Retrieve hass get data method initiatedā¦
Yer i must have copied the wrong bit its still no go for matching consumption to forcast today. But tomorrow it will assume i did the same as today and will be accurate.
My p_load_forecast isnāt that good. So my self_consumption is lower as expected with sunny days as I have a 15 kWh battery. I now use the machine learning forecaster with a history of 117 days and the var_model = sensor.power_load_no_var_loads, is there anyway to get a better fit? When I tune the model the number of optimal lags is 70 and I use 96 lags, so I get an error. My pv_forecast is updated every 15 min, hence the 96 lags.
I could step down to 30 min. and use @markpurcell method fi_fo_buffer for the power_load_no_var_loads, but I prefer the 15 min update as I pay for this service. Or maybe it doesnāt matter that much? Anyone any suggestions? For the rest the EMHASS works nicely.
Sorry, I have misread your first post. I thought you were including load_power_forecast in your payload.
The only way I have been able to get sensor.load_power_forecast to match the now value is by including the relevant now value on the load_power_forecast payload. EMHASS has access to the sensor.power_load_no_var_load, but doesnāt seem to utilise it directly with alpha=1.
Creating the load_power_forecast payload is not simple. I use the now/current value for the first element of the array and then grab historic values from a FIFO buffer I update each 30 minutes.
I suspect this may be a bug in EMHASS as with alpha=1 it should set sensor.load_power_forecast to the current value of power_load_no_var_load, without modification.
Does anyone have a template for a charger for an electric car that takes into account a specified end time and how many timeslots exist in emhass that show the number of endsteps?
Iām trying to think of how to format it but canāt.
I have all other data (see image)
Hi Johan,
I think my charging method might be a good place for you to start, of course needs adjustment to your vairable names, kwhās, charging capacity etc.
#percentage of charge we can add to a max of 90%, based on the volvo integration
- platform: template
sensors:
xc40_additional_charge_percentage:
unit_of_measurement: "%"
device_class: power_factor
value_template: >
{% set current_charge = states('sensor.volvo_yv1x778_battery_charge_level') | int(0) %}
{% if current_charge >= 90 %}
{{ 0 }}
{% else %}
{{ (90 - current_charge) }}
{% endif %}
#multiplied by battery capacity 67 khw
- platform: template
sensors:
xc40_additional_charge_kwh:
unit_of_measurement: "kWh"
device_class: energy
value_template: >
{{ 67 * (states('sensor.xc40_additional_charge_percentage') | int) / 100 }}
#charging with a max of 6kwh
- platform: template
sensors:
xc40_additional_charge_hours:
unit_of_measurement: "h"
device_class: duration
value_template: >
{{ ((states('sensor.xc40_additional_charge_kwh') | float) / 6.0) | round(0, "ceil", 0) }}
#check the easee charger if the car is connected, otherwise the number of hours is 0
- platform: template
sensors:
xc40_additional_charge_hours_if_conncted:
unit_of_measurement: "h"
device_class: duration
value_template: >
{{ (states('sensor.xc40_additional_charge_hours') |int if (states('sensor.ec68ea5q_status') in ("awaiting_start", "ready_to_charge", "charging" )) else 0) }}
- platform: template
sensors:
xc40_additional_charge_watts:
unit_of_measurement: "w"
device_class: power
value_template: >
{{ min(6700, ((states('sensor.xc40_additional_charge_kwh') | float) / 6.0) * 6700) | round(0, "ceil", 0) }}
# needs to be ready at 8am, how many hours till then
- platform: template
sensors:
hours_until_next_8am:
friendly_name: "Hours Until Next 8 AM"
unit_of_measurement: "h"
device_class: duration
value_template: >-
{% if now().hour >= 8 %}
{{ (24 - now().hour + 7) + (0 if now().minute > 30 else 1) }}
{% else %}
{{ (8 - now().hour) + (0 if now().minute > 30 else 1) }}
{% endif %}
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Thanks, Iāll try. The biggest challenge is that my timeslots change every day from 24-11 as I donāt get tomorrowās prices until 13:30. But of course it works if I charge at night. However, sometimes you want to charge directly.
I do something similar. But perform the calculations as part of the rest command.
Summary of User Inputs and Behavior:
-
User Inputs:
input_number.mg_emhass_charge_to_soc: Desired state of charge (SOC) for the EV.sensor.mg_soc: Current SOC of the EV.sensor.mg_soc_kwh: Current battery capacity in kWh.input_number.mg_emhass_charge_by_time: Desired end time for charging.binary_sensor.mg_connected_to_charger: Indicates whether the EV is connected to the charger.
-
Behavior:
- The template calculates the required charging duration (
charge_hours) based on the difference between the current and desired SOC, the EVās battery capacity, and the chargerās rate and efficiency. - It adjusts the charging schedule to align with EMHASS scheduling intervals (30-minute steps).
- If the EV is not currently connected to the charger, the start time is shifted by a default assumption of 2 hours.
- The template then computes the start and end timesteps for charging within the available time frame, ensuring that charging can be completed within the user-specified window. It also adjusts charging parameters to optimize for the available time.
- The template calculates the required charging duration (
Detailed Explanation:
-
Desired SOC and Current SOC:
- The desired SOC is fetched from
input_number.mg_emhass_charge_to_socand converted to a fraction (e.g., 80% becomes 0.8). - The current SOC is similarly fetched from
sensor.mg_socand converted to a fraction.
- The desired SOC is fetched from
-
Calculating Required Energy:
- The total capacity of the battery in kWh is calculated using the current SOC and the corresponding energy in kWh (
sensor.mg_soc_kwh). - The required kWh to reach the desired SOC is calculated by multiplying the difference between the desired and current SOC by the total battery capacity.
- The total capacity of the battery in kWh is calculated using the current SOC and the corresponding energy in kWh (
-
Charging Duration Calculation:
- The charging rate is set to 7400W (7.4 kW), typical for a home EV charger.
- The efficiency of the charger is assumed to be 90% (0.9).
- The charging duration (
charge_hours) is computed by dividing the required kWh by the effective charging power and rounding up to the nearest integer. If no charging is required, it defaults to 0.
-
Determining Charging Schedule:
- The template then determines the end hour by which charging must be completed, based on
input_number.mg_emhass_charge_by_time. - The current time is fetched, and the remaining time until the desired end hour is calculated in minutes, converted to EMHASS scheduling timesteps (each timestep representing 30 minutes).
- If the current hour is past the desired end hour, the calculation accounts for the time wrap-around (from current time to midnight and then to the desired end hour).
- The template then determines the end hour by which charging must be completed, based on
-
Handling EV Connection Status:
- If the EV is not connected to the charger, the template assumes a default 2-hour delay before charging can start.
- If connected, charging can start immediately (
start_time_shift= 0).
-
Final Adjustments to Charging Parameters:
- The template checks if the available time (from start to end timestep) is sufficient to meet the required charging duration.
- If not, it adjusts the
charge_hoursto fit within the available time, ensuring maximum charging can occur within the userās constraints.
-
Output:
- The calculated values are then outputted as:
def_total_hours: Total hours needed for charging.P_deferrable_nom: Nominal charging power.treat_def_as_semi_contandset_def_constant: Flags related to EMHASS settings.def_start_timestep: Start timestep for charging.def_end_timestep: End timestep for charging.
- The calculated values are then outputted as:
This Jinja template is carefully designed to calculate and optimize the EV charging schedule within the constraints defined by the user, such as the desired SOC and the preferred end time, while considering the EVās current SOC and charging rate.
ChatGPT can make mistakes - but it did okay explaining the template!
"num_def_loads": 1,
{% set desired_soc = states('input_number.mg_emhass_charge_to_soc') | float / 100 %}
{% set current_soc = states('sensor.mg_soc') | float / 100 %}
{% set total_capacity_kwh = states('sensor.mg_soc_kwh') | float / current_soc %}
{% set required_kwh = (desired_soc - current_soc) * total_capacity_kwh %}
{% set charger_rate_w = 7400 %}
{% set charger_efficiency = 0.9 %}
{# must be >= 0 and int (round up) #}
{% set charge_hours = [0, ((required_kwh * 1000 / (charger_rate_w * charger_efficiency)) + 0.5) | round(0) | int ] | max %}
{# Convert the charging end hour from mg_emhass_charge_by_time to a timestep aligned with EMHASS scheduling. #}
{% set end_hour = states('input_number.mg_emhass_charge_by_time') | int %}
{% set current_time = now() %}
{% set current_hour = current_time.hour %}
{% set current_minute = current_time.minute %}
{% if current_hour <= end_hour %}
{% set remaining_hours = end_hour - current_hour - 1 %}
{% set remaining_minutes = 60 - current_minute %}
{% set total_minutes = remaining_hours * 60 + remaining_minutes %}
{% set def_end_timestep = (total_minutes / 30) | round(0) %}
{% else %}
{% set def_end_timestep = (24 - current_hour + (current_minute/60) + end_hour - 1) * 2 %}
{% endif %}
{% set def_end_timestep = [def_end_timestep, min_length] | min | int %}
{% if is_state('binary_sensor.mg_connected_to_charger', 'off') %}
{# assume MG will be back and plugged in, in two hours (4 30min slots#}
{% set start_time_shift = 4 %}
{% else %}
{% set start_time_shift = 0 %}
{% endif %}
{% if (def_end_timestep - start_time_shift) < charge_hours * 2 %}
{# can't solve if there isn't enough hours between start and end so reduce charge_hours to maximise charge #}
{% set charge_hours = (def_end_timestep - start_time_shift) / 2 %}
{% endif %}
"def_total_hours": {{[ charge_hours ]}},
"P_deferrable_nom": {{ [charger_rate_w] }},
"treat_def_as_semi_cont": [0],
"set_def_constant": [0],
"def_start_timestep": [{{start_time_shift}}],
"def_end_timestep": [{{ def_end_timestep }}],
1 Like
How is it we create a Fifo buffer? Im completely lost with this, i cant even find it in the emhass user manual
1 Like