* Tests for class_load_container v2
- file as same name as class
- useless numpy conversations removed
- switched to built-in type tests
- human readable tests included
* ruff
* removed dupicate empty list
* load_aggregator: collections.abc.Sequence
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Co-authored-by: Dominique Lasserre <lasserre.d@gmail.com>
Extend single_test_optimization.py to be able to use real world data from new prediction classes.
- .venv/bin/python single_test_optimization.py --real_world --verbose
Can also be run with profiling "--profile".
Add single_test_prediction.py to fetch predictions from remote prediction providers
- .venv/bin/python single_test_prediction.py --verbose --provider-id PVForecastAkkudoktor | more
- .venv/bin/python single_test_prediction.py --verbose --provider-id LoadAkkudoktor | more
- .venv/bin/python single_test_prediction.py --verbose --provider-id ElecPriceAkkudoktor | more
- .venv/bin/python single_test_prediction.py --verbose --provider-id BrightSky | more
- .venv/bin/python single_test_prediction.py --verbose --provider-id ClearOutside | more
Can also be run with profiling "--profile".
single_test_optimization.py is an example on how to retrieve prediction data for optimization and
use it to set up the optimization parameters.
Changes:
- load: Only one load provider at a time (vs. 5 before)
Bug fixes:
- prediction: only use providers that are enabled to retrieve or set data.
- prediction: fix pre pendulum format strings
- dataabc: Prevent error when resampling data with no datasets.
Signed-off-by: Bobby Noelte <b0661n0e17e@gmail.com>
* optimization states for AC, DC and IDLE now similar probab. Also AC states taken from config. Maybe a single config option for AC and E-Auto States is sensefull.
* Ruff
* test_class_optimize: Update testdata
* Write pdf and json to test/testdata/new.... so it can be analyzed
manually or just copied as new expected result.
* workflow: Upload pytest optimization result artifacts (pdf, json)
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Co-authored-by: Andreas <drbacke@gmx.de>
* optimization states for AC, DC and IDLE now similar probab. Also AC states taken from config. Maybe a single config option for AC and E-Auto States is sensefull.
* test_class_optimize: Update testdata
* Write pdf and json to test/testdata/new.... so it can be analyzed
manually or just copied as new expected result.
* workflow: Upload pytest optimization result artifacts (pdf, json)
* Update utilities in utils submodule.
* Add base configuration modules.
* Add server base configuration modules.
* Add devices base configuration modules.
* Add optimization base configuration modules.
* Add utils base configuration modules.
* Add prediction abstract and base classes plus tests.
* Add PV forecast to prediction submodule.
The PV forecast modules are adapted from the class_pvforecast module and
replace it.
* Add weather forecast to prediction submodule.
The modules provide classes and methods to retrieve, manage, and process weather forecast data
from various sources. Includes are structured representations of weather data and utilities
for fetching forecasts for specific locations and time ranges.
BrightSky and ClearOutside are currently supported.
* Add electricity price forecast to prediction submodule.
* Adapt fastapi server to base config and add fasthtml server.
* Add ems to core submodule.
* Adapt genetic to config.
* Adapt visualize to config.
* Adapt common test fixtures to config.
* Add load forecast to prediction submodule.
* Add core abstract and base classes.
* Adapt single test optimization to config.
* Adapt devices to config.
Signed-off-by: Bobby Noelte <b0661n0e17e@gmail.com>
