fix: load data for automatic optimization (#731)

Automatic optimization used to take the adjusted load data even if there were no
measurements leading to 0 load values.

Split LoadAkkudoktor into LoadAkkudoktor and LoadAkkudoktorAdjusted. This allows
to select load data either purely from the load data database or load data additionally
adjusted by load measurements. Some value names have been adapted to denote
also the unit of a value.

For better load bug squashing the optimization solution data availability was
improved. For better data visbility prediction data can now be distinguished from
solution data in the generic optimization solution.

Some predictions that may be of interest to understand the solution were added.

Documentation was updated to resemble the addition load prediction provider and
the value name changes.

Signed-off-by: Bobby Noelte <b0661n0e17e@gmail.com>

single_test_prediction.py

@@ -148,11 +148,11 @@ def run_prediction(provider_id: str, verbose: bool = False) -> str:
         forecast = "elecprice"
     elif provider_id in ("FeedInTariffFixed",):
         settings = config_feedintarifffixed()
-        forecast = "elecprice"
+        forecast = "feedintariff"
     elif provider_id in ("LoadAkkudoktor",):
-        settings = config_elecprice()
-        forecast = "load"
-        settings["load"]["loadakkudoktor_year_energy"] = 1000
+        settings = config_load()
+        forecast = "loadforecast"
+        settings["load"]["LoadAkkudoktor"]["loadakkudoktor_year_energy_wh"] = 1000
     else:
         raise ValueError(f"Unknown provider '{provider_id}'.")
     settings[forecast]["provider"] = provider_id