fix: optimization fail after restart (#1007)
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Fix documentation for the loadforecast_power_w key.

Fix documentation to explain the usage of import file/ JSON string to
primarily initialise prediction data.

Fix code scanning alert no. 6: URL redirection from remote source

Enable to automatically save the configuration to the configuration file
by default, which is a widespread user expectation.

Make the genetic parameters non optional for better pydantic compliance.

Update:
- bump pytest to 9.0.3
- bump pillow to 12.2.0
- bump platformdirs to 4.9.6
- bump typespyyaml to 6.0.12.20260408
- bump tzfpy to 1.2.0
- bump pydantic to 2.13.0
- bump types-requests to 2.33.0.20260408

Signed-off-by: Bobby Noelte <b0661n0e17e@gmail.com>
Co-authored-by: Normann <github@koldrack.com>
This commit is contained in:
Bobby Noelte
2026-04-15 08:48:56 +02:00
committed by GitHub
parent 29cc3d7f3b
commit 6f28022ed0
19 changed files with 717 additions and 671 deletions

View File

@@ -125,6 +125,8 @@
}
},
"general": {
"config_save_mode": "AUTOMATIC",
"config_save_interval_sec": 60,
"version": "0.0.0",
"data_folder_path": "/home/user/.local/share/net.akkudoktoreos.net",
"data_output_subpath": "output",

View File

@@ -9,6 +9,8 @@
| ---- | -------------------- | ---- | --------- | ------- | ----------- |
| config_file_path | | `Optional[pathlib.Path]` | `ro` | `N/A` | Path to EOS configuration file. |
| config_folder_path | | `Optional[pathlib.Path]` | `ro` | `N/A` | Path to EOS configuration directory. |
| config_save_interval_sec | `EOS_GENERAL__CONFIG_SAVE_INTERVAL_SEC` | `int` | `rw` | `60` | Automatic configuration file saving interval [seconds]. |
| config_save_mode | `EOS_GENERAL__CONFIG_SAVE_MODE` | `<enum 'ConfigSaveMode'>` | `rw` | `AUTOMATIC` | Configuration file save mode for configuration changes ['MANUAL', 'AUTOMATIC']. Defaults to 'AUTOMATIC'. |
| data_folder_path | `EOS_GENERAL__DATA_FOLDER_PATH` | `Path` | `rw` | `required` | Path to EOS data folder. |
| data_output_path | | `Optional[pathlib.Path]` | `ro` | `N/A` | Computed data_output_path based on data_folder_path. |
| data_output_subpath | `EOS_GENERAL__DATA_OUTPUT_SUBPATH` | `Optional[pathlib.Path]` | `rw` | `output` | Sub-path for the EOS output data folder. |
@@ -28,6 +30,8 @@
```json
{
"general": {
"config_save_mode": "AUTOMATIC",
"config_save_interval_sec": 60,
"version": "0.0.0",
"data_folder_path": "/home/user/.local/share/net.akkudoktoreos.net",
"data_output_subpath": "output",
@@ -46,6 +50,8 @@
```json
{
"general": {
"config_save_mode": "AUTOMATIC",
"config_save_interval_sec": 60,
"version": "0.0.0",
"data_folder_path": "/home/user/.local/share/net.akkudoktoreos.net",
"data_output_subpath": "output",

View File

@@ -126,7 +126,7 @@
"load": {
"loadimport": {
"import_file_path": null,
"import_json": "{\"load0_mean\": [676.71, 876.19, 527.13]}"
"import_json": "{\"loadforecast_power_w\": [676.71, 876.19, 527.13]}"
}
}
}

View File

@@ -7,10 +7,11 @@
| Name | Environment Variable | Type | Read-Only | Default | Description |
| ---- | -------------------- | ---- | --------- | ------- | ----------- |
| algorithm | `EOS_OPTIMIZATION__ALGORITHM` | `Optional[str]` | `rw` | `GENETIC` | The optimization algorithm. |
| genetic | `EOS_OPTIMIZATION__GENETIC` | `Optional[akkudoktoreos.optimization.optimization.GeneticCommonSettings]` | `rw` | `None` | Genetic optimization algorithm configuration. |
| horizon_hours | `EOS_OPTIMIZATION__HORIZON_HOURS` | `Optional[int]` | `rw` | `24` | The general time window within which the energy optimization goal shall be achieved [h]. Defaults to 24 hours. |
| interval | `EOS_OPTIMIZATION__INTERVAL` | `Optional[int]` | `rw` | `3600` | The optimization interval [sec]. |
| algorithm | `EOS_OPTIMIZATION__ALGORITHM` | `str` | `rw` | `GENETIC` | The optimization algorithm. Defaults to GENETIC |
| genetic | `EOS_OPTIMIZATION__GENETIC` | `GeneticCommonSettings` | `rw` | `required` | Genetic optimization algorithm configuration. |
| horizon | | `int` | `ro` | `N/A` | Number of optimization steps. |
| horizon_hours | `EOS_OPTIMIZATION__HORIZON_HOURS` | `int` | `rw` | `24` | The general time window within which the energy optimization goal shall be achieved [h]. Defaults to 24 hours. |
| interval | `EOS_OPTIMIZATION__INTERVAL` | `int` | `rw` | `3600` | The optimization interval [sec]. Defaults to 3600 seconds (1 hour) |
| keys | | `list[str]` | `ro` | `N/A` | The keys of the solution. |
:::
<!-- pyml enable line-length -->
@@ -58,7 +59,8 @@
"ev_soc_miss": 10
}
},
"keys": []
"keys": [],
"horizon": 24
}
}
```
@@ -73,10 +75,10 @@
| Name | Type | Read-Only | Default | Description |
| ---- | ---- | --------- | ------- | ----------- |
| generations | `Optional[int]` | `rw` | `400` | Number of generations to evaluate the optimal solution [>= 10]. Defaults to 400. |
| individuals | `Optional[int]` | `rw` | `300` | Number of individuals (solutions) to generate for the (initial) generation [>= 10]. Defaults to 300. |
| penalties | `dict[str, Union[float, int, str]]` | `rw` | `required` | A dictionary of penalty function parameters consisting of a penalty function parameter name and the associated value. |
| seed | `Optional[int]` | `rw` | `None` | Fixed seed for genetic algorithm. Defaults to 'None' which means random seed. |
| generations | `Optional[int]` | `rw` | `400` | Number of generations to evolve [>= 10]. Defaults to 400. |
| individuals | `Optional[int]` | `rw` | `300` | Number of individuals (solutions) in the population [>= 10]. Defaults to 300. |
| penalties | `dict[str, Union[float, int, str]]` | `rw` | `required` | Penalty parameters used in fitness evaluation. |
| seed | `Optional[int]` | `rw` | `None` | Random seed for reproducibility. None = random. |
:::
<!-- pyml enable line-length -->

View File

@@ -1,6 +1,6 @@
# Akkudoktor-EOS
**Version**: `v0.3.0.dev2603180781250771`
**Version**: `v0.3.0.dev2604141105859917`
<!-- pyml disable line-length -->
**Description**: This project provides a comprehensive solution for simulating and optimizing an energy system based on renewable energy sources. With a focus on photovoltaic (PV) systems, battery storage (batteries), load management (consumer requirements), heat pumps, electric vehicles, and consideration of electricity price data, this system enables forecasting and optimization of energy flow and costs over a specified period.
@@ -1348,13 +1348,13 @@ Return:
- `application/json`: {
"anyOf": [
{
"$ref": "#/components/schemas/PowerMeasurement-Input"
"$ref": "#/components/schemas/PowerMeasurement"
},
{
"$ref": "#/components/schemas/EnergyMeasurement-Input"
"$ref": "#/components/schemas/EnergyMeasurement"
},
{
"$ref": "#/components/schemas/PPBCPowerProfileStatus-Input"
"$ref": "#/components/schemas/PPBCPowerProfileStatus"
},
{
"$ref": "#/components/schemas/OMBCStatus"
@@ -1363,7 +1363,7 @@ Return:
"$ref": "#/components/schemas/FRBCActuatorStatus"
},
{
"$ref": "#/components/schemas/FRBCEnergyStatus-Input"
"$ref": "#/components/schemas/FRBCEnergyStatus"
},
{
"$ref": "#/components/schemas/FRBCStorageStatus"