How to optimize more than 24 hours?

I'm trying to optimize more than 24h based on nordpool and solcast with 15 minute interval. In this case load_cost_forecast, prod_price_forecast and pv_power_forecast can have a maximum size of 192 items. prediction_horizon is the minimum length of load_cost_forecast, prod_price_forecast or pv_power_forecast. I configured delta_forecast = 2 but get following error when trying MPC:

024-02-11 15:51:20,183 - web_server - ERROR - Exception on /action/naive-mpc-optim [POST]
Traceback (most recent call last):
  File "/usr/local/lib/python3.11/site-packages/flask/app.py", line 1463, in wsgi_app
    response = self.full_dispatch_request()
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/usr/local/lib/python3.11/site-packages/flask/app.py", line 872, in full_dispatch_request
    rv = self.handle_user_exception(e)
         ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/usr/local/lib/python3.11/site-packages/flask/app.py", line 870, in full_dispatch_request
    rv = self.dispatch_request()
         ^^^^^^^^^^^^^^^^^^^^^^^
  File "/usr/local/lib/python3.11/site-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 "/app/src/emhass/web_server.py", line 74, in action_call
    opt_res = naive_mpc_optim(input_data_dict, app.logger)
              ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/usr/local/lib/python3.11/site-packages/emhass-0.7.7-py3.11.egg/emhass/command_line.py", line 265, in naive_mpc_optim
    df_input_data_dayahead = input_data_dict['fcst'].get_load_cost_forecast(
                             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/usr/local/lib/python3.11/site-packages/emhass-0.7.7-py3.11.egg/emhass/forecast.py", line 709, in get_load_cost_forecast
    forecast_out = self.get_forecast_out_from_csv(
                   ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/usr/local/lib/python3.11/site-packages/emhass-0.7.7-py3.11.egg/emhass/forecast.py", line 526, in get_forecast_out_from_csv
    forecast_out = pd.DataFrame(
                   ^^^^^^^^^^^^^
  File "/usr/local/lib/python3.11/site-packages/pandas/core/frame.py", line 758, in __init__
    mgr = ndarray_to_mgr(
          ^^^^^^^^^^^^^^^
  File "/usr/local/lib/python3.11/site-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/site-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 (66, 1), indices imply (33, 1)

If I limit load_cost_forecast and prod_price_forecast to 96 items with delta_forecast = 1 everything works fine. If I limit load_cost_forecast and prod_price_forecast to 96 items with delta_forecast = 2 everything works fine. I'm running EMHASS in docker.

How to predict more than 24 hours?

davidusb-geek / emhass

How to optimize more than 24 hours? #192