EMHASS: An Energy Management for Home Assistant

poupaerta · March 30, 2024, 1:37pm

Somebody has this error (see below)? Everthing worked fine untill this morning. Tried a complete reinstall, but did not help. Also changed the “sensor.pv” and “sensor.home_load_no_var”. But keeps getting the same error. If i run a “day-ahead optimization” or “ML forecast model fit” from the addon web server UI.
Ps. I am from Belgium and tomorrow the clock gets shifted to “daylight savings time”. Don’t know if this is related to the problem.

2024-03-30 14:25:18,524 - web_server - INFO - Passed runtime parameters: {}
2024-03-30 14:25:18,524 - web_server - INFO -  >> Setting input data dict
2024-03-30 14:25:18,525 - web_server - INFO - Setting up needed data
2024-03-30 14:25:18,530 - web_server - ERROR - Exception on /action/dayahead-optim [POST]
Traceback (most recent call last):
  File "/usr/local/lib/python3.11/dist-packages/flask/app.py", line 1463, in wsgi_app
    response = self.full_dispatch_request()
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/usr/local/lib/python3.11/dist-packages/flask/app.py", line 872, in full_dispatch_request
    rv = self.handle_user_exception(e)
         ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/usr/local/lib/python3.11/dist-packages/flask/app.py", line 870, in full_dispatch_request
    rv = self.dispatch_request()
         ^^^^^^^^^^^^^^^^^^^^^^^
  File "/usr/local/lib/python3.11/dist-packages/flask/app.py", line 855, in dispatch_request
    return self.ensure_sync(self.view_functions[rule.endpoint])(**view_args)  # type: ignore[no-any-return]
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/usr/local/lib/python3.11/dist-packages/emhass/web_server.py", line 104, in action_call
    input_data_dict = set_input_data_dict(config_path, str(data_path), costfun,
                     ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/usr/local/lib/python3.11/dist-packages/emhass/command_line.py", line 64, in set_input_data_dict
    fcst = Forecast(retrieve_hass_conf, optim_conf, plant_conf,
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/usr/local/lib/python3.11/dist-packages/emhass/forecast.py", line 162, in __init__
    freq=self.freq).round(self.freq, ambiguous='infer', nonexistent=self.freq)
                    ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/usr/local/lib/python3.11/dist-packages/pandas/core/indexes/extension.py", line 98, in method
    result = attr(self._data, *args, **kwargs)
             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/usr/local/lib/python3.11/dist-packages/pandas/core/arrays/datetimelike.py", line 2026, in round
    return self._round(freq, RoundTo.NEAREST_HALF_EVEN, ambiguous, nonexistent)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/usr/local/lib/python3.11/dist-packages/pandas/core/arrays/datetimelike.py", line 2002, in _round
    return result.tz_localize(
           ^^^^^^^^^^^^^^^^^^^
  File "/usr/local/lib/python3.11/dist-packages/pandas/core/arrays/_mixins.py", line 86, in method
    return meth(self, *args, **kwargs)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/usr/local/lib/python3.11/dist-packages/pandas/core/arrays/datetimes.py", line 1040, in tz_localize
    new_dates = tzconversion.tz_localize_to_utc(
                ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "pandas/_libs/tslibs/tzconversion.pyx", line 380, in pandas._libs.tslibs.tzconversion.tz_localize_to_utc
ValueError: The provided timedelta will relocalize on a nonexistent time: 0 days 00:30:00

Ps. I see that an issue has been raised on Github concerning daylight savings time. If i need to remove this post, let me know.

davidusb · March 30, 2024, 9:13pm

Brace yourselves, DST is coming!
While I did tried to make the code to survive DST as much as I can its still not 100% guaranteed.
I suggest to closely keep and eye on errors or switch to your classic automations without optimization for a day or two where typically everything goes back to normal. We’ll see

davidusb · March 31, 2024, 7:40am

Finally some people reported some issues and errors. Still some fixing needed for complete DST survival.
However in my case using only dayahead-optim I found no issue whatsoever, 24h optimization ran smoothly this time.

bvm · March 31, 2024, 9:10am

This is the output, looks fine to me?

rest_command:
  dayahead_optim_rest:
    url: http://localhost:5000/action/dayahead-optim
    method: POST
    content_type: "application/json"
    payload: >-
      {
        "prediction_horizon": 48,
        "pv_power_forecast": [3030, 4049, 4635, 4763, 4858, 4657, 4138, 3570, 2963, 2362, 1788, 1388, 1109, 805, 508, 248, 96, 5, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 58, 198, 391, 650, 918, 1234, 1607, 1956, 2299, 2657, 2994, 3334, 3659, 3815, 3804, 3735, 3603, 3313, 2934, 2525, 2119, 1636, 1133, 605, 191, 11, 0, 0, 0, 0, 0, 0, 0], 
        "load_cost_forecast": [0.1601, 0.1601, 0.14119, 0.14119, 0.1389, 0.1389, 0.1529, 0.1529, 0.17687, 0.17687, 0.19969, 0.19969, 0.21037, 0.21037, 0.24432, 0.24432, 0.21895, 0.21895, 0.19164, 0.19164, 0.18784, 0.18784, 0.19539, 0.19539, 0.19874, 0.19874, 0.19874, 0.19874, 0.19874, 0.19874, 0.19874, 0.19874, 0.19874, 0.19874, 0.19874, 0.19874, 0.19874, 0.19874, 0.19874, 0.19874, 0.19874, 0.19874, 0.19874, 0.19874, 0.19874, 0.19874, 0.19874, 0.19874],
        "num_def_loads": 1,
        "def_total_hours": [4],
        "P_deferrable_nom":  [2500],
        "treat_def_as_semi_cont": [0],
        "set_def_constant": [1]
      }

bert1111 · March 31, 2024, 6:34pm

I have this issue also and an other one.
I thought it was my fault(issue started a few days ago) and was waiting for it to clear on it’s own.

ERROR - web_server - Exception on /action/dayahead-optim [POST]
Traceback (most recent call last):
  File "/usr/local/lib/python3.11/dist-packages/flask/app.py", line 1463, in wsgi_app
    response = self.full_dispatch_request()
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/usr/local/lib/python3.11/dist-packages/flask/app.py", line 872, in full_dispatch_request
    rv = self.handle_user_exception(e)
         ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/usr/local/lib/python3.11/dist-packages/flask/app.py", line 870, in full_dispatch_request
    rv = self.dispatch_request()
         ^^^^^^^^^^^^^^^^^^^^^^^
  File "/usr/local/lib/python3.11/dist-packages/flask/app.py", line 855, in dispatch_request
    return self.ensure_sync(self.view_functions[rule.endpoint])(**view_args)  # type: ignore[no-any-return]
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/usr/local/lib/python3.11/dist-packages/emhass/web_server.py", line 104, in action_call
    input_data_dict = set_input_data_dict(config_path, str(data_path), costfun,
                     ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/usr/local/lib/python3.11/dist-packages/emhass/command_line.py", line 93, in set_input_data_dict
    P_load_forecast = fcst.get_load_forecast(method=optim_conf['load_forecast_method'])
                      ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/usr/local/lib/python3.11/dist-packages/emhass/forecast.py", line 626, in get_load_forecast
    data = pd.DataFrame.from_dict(data_dict)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/usr/local/lib/python3.11/dist-packages/pandas/core/frame.py", line 1760, in from_dict
    return cls(data, index=index, columns=columns, dtype=dtype)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/usr/local/lib/python3.11/dist-packages/pandas/core/frame.py", line 709, in __init__
    mgr = dict_to_mgr(data, index, columns, dtype=dtype, copy=copy, typ=manager)
          ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/usr/local/lib/python3.11/dist-packages/pandas/core/internals/construction.py", line 481, in dict_to_mgr
    return arrays_to_mgr(arrays, columns, index, dtype=dtype, typ=typ, consolidate=copy)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/usr/local/lib/python3.11/dist-packages/pandas/core/internals/construction.py", line 115, in arrays_to_mgr
    index = _extract_index(arrays)
            ^^^^^^^^^^^^^^^^^^^^^^
  File "/usr/local/lib/python3.11/dist-packages/pandas/core/internals/construction.py", line 655, in _extract_index
    raise ValueError("All arrays must be of the same length")
ValueError: All arrays must be of the same length

ERROR - web_server - Exception on /action/perfect-optim [POST]
Traceback (most recent call last):
  File "/usr/local/lib/python3.11/dist-packages/pandas/core/arrays/datetimes.py", line 2423, in _infer_tz_from_endpoints
    inferred_tz = timezones.infer_tzinfo(start, end)
                  ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "pandas/_libs/tslibs/timezones.pyx", line 368, in pandas._libs.tslibs.timezones.infer_tzinfo
AssertionError: Inputs must both have the same timezone, UTC+01:00 != UTC+02:00

The above exception was the direct cause of the following exception:

Traceback (most recent call last):
  File "/usr/local/lib/python3.11/dist-packages/flask/app.py", line 1463, in wsgi_app
    response = self.full_dispatch_request()
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/usr/local/lib/python3.11/dist-packages/flask/app.py", line 872, in full_dispatch_request
    rv = self.handle_user_exception(e)
         ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/usr/local/lib/python3.11/dist-packages/flask/app.py", line 870, in full_dispatch_request
    rv = self.dispatch_request()
         ^^^^^^^^^^^^^^^^^^^^^^^
  File "/usr/local/lib/python3.11/dist-packages/flask/app.py", line 855, in dispatch_request
    return self.ensure_sync(self.view_functions[rule.endpoint])(**view_args)  # type: ignore[no-any-return]
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/usr/local/lib/python3.11/dist-packages/emhass/web_server.py", line 119, in action_call
    opt_res = perfect_forecast_optim(input_data_dict, app.logger)
              ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/usr/local/lib/python3.11/dist-packages/emhass/command_line.py", line 207, in perfect_forecast_optim
    opt_res = input_data_dict['opt'].perform_perfect_forecast_optim(df_input_data, input_data_dict['days_list'])
              ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/usr/local/lib/python3.11/dist-packages/emhass/optimization.py", line 538, in perform_perfect_forecast_optim
    data_tp = df_input_data.copy().loc[pd.date_range(start=day_start, end=day_end, freq=self.freq)]
                                       ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/usr/local/lib/python3.11/dist-packages/pandas/core/indexes/datetimes.py", line 945, in date_range
    dtarr = DatetimeArray._generate_range(
            ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/usr/local/lib/python3.11/dist-packages/pandas/core/arrays/datetimes.py", line 422, in _generate_range
    tz = _infer_tz_from_endpoints(start, end, tz)
         ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/usr/local/lib/python3.11/dist-packages/pandas/core/arrays/datetimes.py", line 2426, in _infer_tz_from_endpoints
    raise TypeError(
TypeError: Start and end cannot both be tz-aware with different timezones

davidusb · March 31, 2024, 10:45pm

The first error is the error related to DST. Needs to be worked out. I just applied a new fix.
The second error seems like a bug when dealing with TZ. Will look into it.

davidusb · March 31, 2024, 10:49pm

Dear community I have created a new webapp to try to ease setting up the scrape + PVLib method for PV power forecast. I still believe that this is the more accurate option for PV power forecast. Unfortunately the PV modules and inverter database from PVLib is quite outdated. So I decided to update those databases and to add them directly to EMHASS, I will keep them updated regularly.
So this webapp can be used to search the names of your own module and inverter model in the database.
The EMHASS will be updated in the upcoming days and the following release will include this database directly in the source code.

Here is the link to the webapp: https://emhass-pvlib-database.streamlit.app/

110hs · April 1, 2024, 12:29am

Will this be a brand new DB or will devices available in current PVLib be included as well?
Asking as in the webapp I can’t find an inverter I’m using: SMA_America__SB3000TL_US_22__240V_

davidusb · April 1, 2024, 6:40am

It is an updated database but where you should be able to find the inverter that you were using before, so no change needed if you already found your correct inverter. But you are right, for the inverters I just forgot to merge the old database with the new, so there are some missing keys that were there before. I will fix it, no problem.

davidusb · April 1, 2024, 8:05pm

Done, the new DB are updated

arva · April 2, 2024, 5:33am

@davidusb , from 0.8.5 release notes
:

Added new tests for forecast longer than 24h by changing parameter `delta_forecast

Does that mean we can have a longer forecast now?

davidusb · April 2, 2024, 9:05am

You can now and you could before. Just need to change the delta_forecast parameter in the configuration to the number of days that you want to forecast. I just added some unit tests to test this parameter functionality and check that is working as intended, and it is.

arva · April 2, 2024, 9:19am

Ok. Probably misunderstood. I thought I can make MPC optimization now for example 36h but this is not it.

Use case is that around 2pm each day tomorrow’s Noordpool hourly prices will be public and it would be nice to make optimization until the end of next day.

davidusb · April 2, 2024, 9:21am

Yes you can do MPC for as long as you want. Modify the said delta_forecast parameter and of course the prediction_horizon parameter

arva · April 2, 2024, 9:34am

Interesting, I tried it about a month ago and turned out it can be 24h max.

If I put both prediction horizon and delta for example to 30 (I have hourly data) it should work?

I actually use mlforecast, so the delta forecast is not applicable?

Edit: same issue here EMHASS: An Energy Management for Home Assistant - #1658 by michaelpiron

arva · April 2, 2024, 9:43am

@michaelpiron, did you solve the issue with longer than 24h optimization?

davidusb · April 2, 2024, 10:46am

The MLForecaster will predict to the num_lags that you fixed

gieljnssns · April 2, 2024, 1:38pm

Is there a way to add data from your own inverter? Mine isn’t listed.
I’m using an huawei sun2000-4ktl-m1, all huawei’s that are listed are US versions.
And how do you calculate some of those values that are needed?

arva · April 2, 2024, 2:36pm

@davidusb
When i did try again to forecast next 31 hours i got an ValueError: Shape of passed values is (14, 1), indices imply (7, 1):

2024-04-02 17:30:00,479 - web_server - INFO - Passed runtime parameters: {'load_cost_forecast': [0.07, 0.109, 0.146, 0.173, 0.172, 0.091, 0.071, 0.042, 0.071, 0.065, 0.061, 0.056, 0.073, 0.124, 0.167, 0.199, 0.198, 0.168, 0.158, 0.154, 0.149, 0.146, 0.143, 0.146, 0.15, 0.169, 0.191, 0.206, 0.18, 0.131, 0.115], 'prod_price_forecast': [0.009, 0.041, 0.071, 0.093, 0.093, 0.042, 0.026, 0.002, 0.025, 0.021, 0.017, 0.013, 0.027, 0.069, 0.088, 0.115, 0.114, 0.089, 0.081, 0.077, 0.074, 0.071, 0.069, 0.071, 0.075, 0.09, 0.108, 0.12, 0.099, 0.075, 0.061], 'prediction_horizon': 31, 'pv_power_forecast': [376, 232, 72, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 3, 151, 459, 907, 1427, 1844, 2111, 2195, 2108, 1958, 1461, 835, 410, 121, 0, 0, 0, 0], 'var_model': 'sensor.ss_load_power', 'var_load:': 'sensor.ss_load_power', 'delta_forecast': 20}
2024-04-02 17:30:00,480 - web_server - INFO -  >> Setting input data dict
2024-04-02 17:30:00,480 - web_server - INFO - Setting up needed data
2024-04-02 17:30:00,483 - web_server - INFO - Retrieve hass get data method initiated...
2024-04-02 17:30:00,799 - web_server - INFO - Retrieving weather forecast data using method = list
2024-04-02 17:30:00,801 - web_server - INFO - Retrieving data from hass for load forecast using method = mlforecaster
2024-04-02 17:30:00,801 - web_server - INFO - Retrieve hass get data method initiated...
2024-04-02 17:30:01,626 - web_server - INFO -  >> Performing naive MPC optimization...
2024-04-02 17:30:01,626 - web_server - INFO - Performing naive MPC optimization
2024-04-02 17:30:01,633 - web_server - ERROR - Exception on /action/naive-mpc-optim [POST]
Traceback (most recent call last):
  File "/usr/local/lib/python3.11/dist-packages/flask/app.py", line 1463, in wsgi_app
    response = self.full_dispatch_request()
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/usr/local/lib/python3.11/dist-packages/flask/app.py", line 872, in full_dispatch_request
    rv = self.handle_user_exception(e)
         ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/usr/local/lib/python3.11/dist-packages/flask/app.py", line 870, in full_dispatch_request
    rv = self.dispatch_request()
         ^^^^^^^^^^^^^^^^^^^^^^^
  File "/usr/local/lib/python3.11/dist-packages/flask/app.py", line 855, in dispatch_request
    return self.ensure_sync(self.view_functions[rule.endpoint])(**view_args)  # type: ignore[no-any-return]
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/usr/local/lib/python3.11/dist-packages/emhass/web_server.py", line 145, in action_call
    opt_res = naive_mpc_optim(input_data_dict, app.logger)
              ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/usr/local/lib/python3.11/dist-packages/emhass/command_line.py", line 273, in naive_mpc_optim
    df_input_data_dayahead = input_data_dict['fcst'].get_load_cost_forecast(
                             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/usr/local/lib/python3.11/dist-packages/emhass/forecast.py", line 715, in get_load_cost_forecast
    forecast_out = self.get_forecast_out_from_csv(
                   ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/usr/local/lib/python3.11/dist-packages/emhass/forecast.py", line 530, in get_forecast_out_from_csv
    forecast_out = pd.DataFrame(
                   ^^^^^^^^^^^^^
  File "/usr/local/lib/python3.11/dist-packages/pandas/core/frame.py", line 758, in __init__
    mgr = ndarray_to_mgr(
          ^^^^^^^^^^^^^^^
  File "/usr/local/lib/python3.11/dist-packages/pandas/core/internals/construction.py", line 337, in ndarray_to_mgr
    _check_values_indices_shape_match(values, index, columns)
  File "/usr/local/lib/python3.11/dist-packages/pandas/core/internals/construction.py", line 408, in _check_values_indices_shape_match
    raise ValueError(f"Shape of passed values is {passed}, indices imply {implied}")
ValueError: Shape of passed values is (14, 1), indices imply (7, 1)

There is data for each input for 31 hours.

Also MLforecast fit gave me error:

2024-04-02 17:35:51,930 - web_server - INFO - Passed runtime parameters: {'days_to_retrieve': 20, 'model_type': 'load_forecast', 'var_model': 'sensor.ss_load_power', 'num_lags': 24, 'split_date_delta': '48h', 'perform_backtest': 'True'}
2024-04-02 17:35:51,930 - web_server - INFO -  >> Setting input data dict
2024-04-02 17:35:51,930 - web_server - INFO - Setting up needed data
2024-04-02 17:35:51,933 - web_server - INFO - Retrieve hass get data method initiated...
2024-04-02 17:35:51,937 - web_server - ERROR - The retrieved JSON is empty, A sensor:sensor.ss_load_power may have 0 days of history or passed sensor may not be correct

Could it be because of daylight saving time? Error occured after updating to 0.8.5

i do have data in sensor.ss_load_power

EDIT: Also dayahead is not working:

2024-04-02 17:40:07,717 - web_server - INFO - Passed runtime parameters: {'load_cost_forecast': [0.07, 0.109, 0.146, 0.173, 0.172, 0.091, 0.071, 0.042, 0.071, 0.065, 0.061, 0.056, 0.073, 0.124, 0.167, 0.199, 0.198, 0.168, 0.158, 0.154, 0.149, 0.146, 0.143, 0.146], 'prod_price_forecast': [0.009, 0.041, 0.071, 0.093, 0.093, 0.042, 0.026, 0.002, 0.025, 0.021, 0.017, 0.013, 0.027, 0.069, 0.088, 0.115, 0.114, 0.089, 0.081, 0.077, 0.074, 0.071, 0.069, 0.071], 'prediction_horizon': 24, 'pv_power_forecast': [376, 232, 72, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 3, 151, 459, 907, 1427, 1844, 2111, 2195, 2108, 1958, 1461, 835, 410, 121, 0, 0, 0, 0], 'var_model': 'sensor.ss_load_power', 'var_load:': 'sensor.ss_load_power', 'delta_forecast': 20}
2024-04-02 17:40:07,717 - web_server - INFO -  >> Setting input data dict
2024-04-02 17:40:07,718 - web_server - INFO - Setting up needed data
2024-04-02 17:40:07,722 - web_server - ERROR - ERROR: The passed data is either not a list or the length is not correct, length should be 48
2024-04-02 17:40:07,723 - web_server - ERROR - Passed type is <class 'list'> and length is 31
2024-04-02 17:40:07,723 - web_server - ERROR - ERROR: The passed data is either not a list or the length is not correct, length should be 48
2024-04-02 17:40:07,724 - web_server - ERROR - Passed type is <class 'list'> and length is 24
2024-04-02 17:40:07,724 - web_server - ERROR - ERROR: The passed data is either not a list or the length is not correct, length should be 48
2024-04-02 17:40:07,724 - web_server - ERROR - Passed type is <class 'list'> and length is 24
2024-04-02 17:40:07,735 - web_server - INFO - Retrieving weather forecast data using method = scrapper
2024-04-02 17:40:08,717 - web_server - ERROR - Exception on /action/dayahead-optim [POST]
Traceback (most recent call last):
  File "/usr/local/lib/python3.11/dist-packages/flask/app.py", line 1463, in wsgi_app
    response = self.full_dispatch_request()
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/usr/local/lib/python3.11/dist-packages/flask/app.py", line 872, in full_dispatch_request
    rv = self.handle_user_exception(e)
         ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/usr/local/lib/python3.11/dist-packages/flask/app.py", line 870, in full_dispatch_request
    rv = self.dispatch_request()
         ^^^^^^^^^^^^^^^^^^^^^^^
  File "/usr/local/lib/python3.11/dist-packages/flask/app.py", line 855, in dispatch_request
    return self.ensure_sync(self.view_functions[rule.endpoint])(**view_args)  # type: ignore[no-any-return]
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/usr/local/lib/python3.11/dist-packages/emhass/web_server.py", line 108, in action_call
    input_data_dict = set_input_data_dict(config_path, str(data_path), costfun,
                     ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/usr/local/lib/python3.11/dist-packages/emhass/command_line.py", line 91, in set_input_data_dict
    df_weather = fcst.get_weather_forecast(method=optim_conf['weather_forecast_method'])
                 ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/usr/local/lib/python3.11/dist-packages/emhass/forecast.py", line 210, in get_weather_forecast
    raw_data.set_index(forecast_dates_scrap, inplace=True)
  File "/usr/local/lib/python3.11/dist-packages/pandas/core/frame.py", line 5910, in set_index
    raise ValueError(
ValueError: Length mismatch: Expected 24 rows, received array of length 48

davidusb · April 2, 2024, 3:00pm

No we can’t add new items to the list. The parameters are fitted by the NREL and other labs from experimental data.
But the DB is pretty big, for example in your case this one will do the trick I guess: Huawei_Technologies_Co___Ltd___SUN2000_11_4KTL_USL0__240V_