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7 | 7 |
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8 | 8 | | Name | Environment Variable | Type | Read-Only | Default | Description | |
9 | 9 | | ---- | -------------------- | ---- | --------- | ------- | ----------- | |
10 | | -| algorithm | `EOS_OPTIMIZATION__ALGORITHM` | `Optional[str]` | `rw` | `GENETIC` | The optimization algorithm. | |
11 | | -| genetic | `EOS_OPTIMIZATION__GENETIC` | `Optional[akkudoktoreos.optimization.optimization.GeneticCommonSettings]` | `rw` | `None` | Genetic optimization algorithm configuration. | |
12 | | -| 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. | |
13 | | -| interval | `EOS_OPTIMIZATION__INTERVAL` | `Optional[int]` | `rw` | `3600` | The optimization interval [sec]. | |
| 10 | +| algorithm | `EOS_OPTIMIZATION__ALGORITHM` | `str` | `rw` | `GENETIC` | The optimization algorithm. Defaults to GENETIC | |
| 11 | +| genetic | `EOS_OPTIMIZATION__GENETIC` | `GeneticCommonSettings` | `rw` | `required` | Genetic optimization algorithm configuration. | |
| 12 | +| horizon | | `int` | `ro` | `N/A` | Number of optimization steps. | |
| 13 | +| 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. | |
| 14 | +| interval | `EOS_OPTIMIZATION__INTERVAL` | `int` | `rw` | `3600` | The optimization interval [sec]. Defaults to 3600 seconds (1 hour) | |
14 | 15 | | keys | | `list[str]` | `ro` | `N/A` | The keys of the solution. | |
15 | 16 | ::: |
16 | 17 | <!-- pyml enable line-length --> |
|
58 | 59 | "ev_soc_miss": 10 |
59 | 60 | } |
60 | 61 | }, |
61 | | - "keys": [] |
| 62 | + "keys": [], |
| 63 | + "horizon": 24 |
62 | 64 | } |
63 | 65 | } |
64 | 66 | ``` |
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73 | 75 |
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74 | 76 | | Name | Type | Read-Only | Default | Description | |
75 | 77 | | ---- | ---- | --------- | ------- | ----------- | |
76 | | -| generations | `Optional[int]` | `rw` | `400` | Number of generations to evaluate the optimal solution [>= 10]. Defaults to 400. | |
77 | | -| individuals | `Optional[int]` | `rw` | `300` | Number of individuals (solutions) to generate for the (initial) generation [>= 10]. Defaults to 300. | |
78 | | -| 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. | |
79 | | -| seed | `Optional[int]` | `rw` | `None` | Fixed seed for genetic algorithm. Defaults to 'None' which means random seed. | |
| 78 | +| generations | `Optional[int]` | `rw` | `400` | Number of generations to evolve [>= 10]. Defaults to 400. | |
| 79 | +| individuals | `Optional[int]` | `rw` | `300` | Number of individuals (solutions) in the population [>= 10]. Defaults to 300. | |
| 80 | +| penalties | `dict[str, Union[float, int, str]]` | `rw` | `required` | Penalty parameters used in fitness evaluation. | |
| 81 | +| seed | `Optional[int]` | `rw` | `None` | Random seed for reproducibility. None = random. | |
80 | 82 | ::: |
81 | 83 | <!-- pyml enable line-length --> |
82 | 84 |
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