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feat: integrate device and runtime configuration foundation on main (#1328)

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* feat: adapt configuration for multi optimization algorithms

Decouple configuration from optimization algorithm parameters. Add to_[algorithm]_param() methods
to the configuration that derive optimization algorithm specific parameters from the configuration.
Add x-scope tags to the configuration options that describe for which specific algorithms the
configuration option is for.

The whole device settings are restructured. There are now general settings for the device classes
with the afore mentioned to_[algorithm]_param() methods. The general device settings got their own
directory `devices/settings`. By this the parameter class also does not have to be a pydantic model
which can be used for future optimization/ simulations speed up.

Also the parameter class for a device is now part of the device module. This better decouples and
also is the natural place for parameters of a device.

Besides this feature there are also fixes and improvements:

* feat: extend home appliance time window settings and simulation

  Home appliance can now be configured for multiple runs with per-cycle allowed time windows. The
  number of remaining cycles to plan is determined at runtime by reading the
  ``cycles_completed_measurement_key`` from the measurement store.

* feat: specialiced CycleTimeWindowSequence for time window sequences

  Sequence of time windows associated to cycles.

  This model specializes ``ValueTimeWindowSequence`` so that the ``value``
  field of each ``ValueTimeWindow`` encodes the **cycle index** (0-based
  integer) the window belongs to.

  Typical use: an appliance that must run ``n`` times per day, each run
  constrained to a distinct time window.  Assign ``value=0`` to windows
  for the first cycle, ``value=1`` for the second, and so on.  Multiple
  windows may share the same cycle index (their allowed regions are unioned).
  Windows with ``value=None`` are silently ignored by all cycle-aware methods.

* fix: Make test_configmigrate also regard the _ANY_SENTENIEL in key values

* chore: Make devices configurations a map instead of a list

  This makes config paths stable regardless of declaration order and lets each device settings
  class build its own config path from ``self.device_id`` without needing an external index.
  Tests are adapted likewise.

  Devices configurations are automatically migrated from lists to maps.

* chore: rename levelized_cost_of_storage_kwh to levelized_cost_of_storage_amt kwh

  This better fits in the naming scheme and also makes clear the costs are money.

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

* fix: runtime config update ignored by config file

Runtime settings were handed back to pydantic-settings as init settings,
which rank below the config file and the environment. Any key already
present in EOS.config.json or in the environment silently discarded the
update, so a bulk PUT /v1/config returned 200 without applying anything,
while the granular PUT /v1/config/{path} endpoint kept working.

Add a dedicated runtime settings source ranked directly below the command
line arguments and record granular updates there as well, so both
endpoints share one store that survives re-evaluation of the settings
sources. Environment variables keep precedence over the config file for
all keys that were not set at runtime.

Also repairs revert_settings() and update(), which passed their data
through the same init settings.

Closes #1303

* fix: env vars ignored on first config build

ConfigEOS.__init__ passed self as first positional argument to _setup,
which forwards it to pydantic_settings.BaseSettings.__init__. Its first
positional parameter is _case_sensitive, so the environment source
matched the upper case variable names against the lower case field names
and returned nothing. Environment settings only took effect after the
next configuration setup.

* docs: changelog for config priority fixes

* fix(config): preserve device identities and storage costs during migration

* fix(devices): preserve charge-rate typing and public import compatibility

* ruff format fix

* fix(config): satisfy typed device conversion and migration contracts

* docs(config): refresh validated configuration prerequisite schemas

---------

Signed-off-by: Bobby Noelte <b0661n0e17e@gmail.com>
Co-authored-by: Bobby Noelte <b0661n0e17e@gmail.com>
Co-authored-by: r0b2g1t <r0b2g1t@users.noreply.github.com>
This commit is contained in:
Andreas
2026-09-17 17:51:40 +02:00
committed by GitHub
co-authored by Bobby Noelte r0b2g1t
parent 431d7d57e5
commit 8224c64654
55 changed files with 5214 additions and 2170 deletions
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src/akkudoktoreos/devices/devices.py
+96 -293
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@@ -1,354 +1,157 @@
"""General configuration settings for simulated devices for optimization."""
import json
import re
from typing import Any, Optional, TextIO, cast
import numpy as np
from loguru import logger
from numpydantic import NDArray, Shape
from pydantic import Field, computed_field, field_validator, model_validator
from akkudoktoreos.config.configabc import SettingsBaseModel, TimeWindowSequence
from akkudoktoreos.config.configabc import ConfigScope, SettingsBaseModel
from akkudoktoreos.core.cache import CacheFileStore
from akkudoktoreos.core.coreabc import ConfigMixin, SingletonMixin
from akkudoktoreos.core.emplan import ResourceStatus
from akkudoktoreos.core.pydantic import ConfigDict, PydanticBaseModel
from akkudoktoreos.devices.devicesabc import DevicesBaseSettings
from akkudoktoreos.devices.settings.batterysettings import (
BATTERY_DEFAULT_CHARGE_RATES as BATTERY_DEFAULT_CHARGE_RATES,
)
from akkudoktoreos.devices.settings.batterysettings import (
BatteriesCommonSettings,
)
from akkudoktoreos.devices.settings.homeappliancesettings import (
HomeApplianceCommonSettings,
)
from akkudoktoreos.devices.settings.invertersettings import InverterCommonSettings
from akkudoktoreos.utils.datetimeutil import DateTime, to_datetime
# Default charge rates for battery
BATTERY_DEFAULT_CHARGE_RATES: list[float] = [0.0, 0.1, 0.2, 0.3, 0.4, 0.5, 0.6, 0.7, 0.8, 0.9, 1.0]
class BatteriesCommonSettings(DevicesBaseSettings):
"""Battery devices base settings."""
capacity_wh: int = Field(
default=8000, gt=0, json_schema_extra={"description": "Capacity [Wh].", "examples": [8000]}
)
charging_efficiency: float = Field(
default=0.88,
gt=0,
le=1,
json_schema_extra={
"description": "Charging efficiency [0.01 ... 1.00].",
"examples": [0.88],
},
)
discharging_efficiency: float = Field(
default=0.88,
gt=0,
le=1,
json_schema_extra={
"description": "Discharge efficiency [0.01 ... 1.00].",
"examples": [0.88],
},
)
levelized_cost_of_storage_kwh: float = Field(
default=0.0,
json_schema_extra={
"description": "Levelized cost of storage (LCOS), the average lifetime cost of delivering one kWh [amount/kWh].",
"examples": [0.12],
},
)
max_charge_power_w: Optional[float] = Field(
default=5000,
gt=0,
json_schema_extra={"description": "Maximum charging power [W].", "examples": [5000]},
)
min_charge_power_w: Optional[float] = Field(
default=50,
gt=0,
json_schema_extra={"description": "Minimum charging power [W].", "examples": [50]},
)
charge_rates: Optional[list[float]] = Field(
default=BATTERY_DEFAULT_CHARGE_RATES,
json_schema_extra={
"description": (
"Charge rates as factor of maximum charging power [0.00 ... 1.00]. "
"None triggers fallback to default charge-rates."
),
"examples": [[0.0, 0.25, 0.5, 0.75, 1.0], None],
},
)
min_soc_percentage: int = Field(
default=0,
ge=0,
le=100,
json_schema_extra={
"description": (
"Minimum state of charge (SOC) as percentage of capacity [%]. "
"This is the target SoC for charging"
),
"examples": [10],
},
)
max_soc_percentage: int = Field(
default=100,
ge=0,
le=100,
json_schema_extra={
"description": "Maximum state of charge (SOC) as percentage of capacity [%].",
"examples": [100],
},
)
@field_validator("charge_rates", mode="before")
def validate_and_sort_charge_rates(cls, v: Any) -> NDArray[Shape["*"], float]:
# None means fallback to default values
if v is None:
return np.asarray(BATTERY_DEFAULT_CHARGE_RATES, dtype=float)
# Convert to numpy array
if isinstance(v, str):
# Remove brackets and split by comma or whitespace
numbers = re.split(r"[,\s]+", v.strip("[]"))
# Filter out any empty strings and convert to floats
arr = np.array([float(x) for x in numbers if x])
else:
arr = np.array(v, dtype=float)
# Must not be empty
if arr.size == 0:
raise ValueError("charge_rates must contain at least one value.")
# Enforce bounds: 0.0 ≤ x ≤ 1.0
if (arr < 0.0).any() or (arr > 1.0).any():
raise ValueError("charge_rates must be within [0.0, 1.0].")
# Remove duplicates + sort
arr = np.unique(arr)
arr.sort()
return arr
@computed_field # type: ignore[prop-decorator]
@property
def measurement_key_soc_factor(self) -> str:
"""Measurement key for the battery state of charge (SoC) as factor of total capacity [0.0 ... 1.0]."""
return f"{self.device_id}-soc-factor"
@computed_field # type: ignore[prop-decorator]
@property
def measurement_key_power_l1_w(self) -> str:
"""Measurement key for the L1 power the battery is charged or discharged with [W]."""
return f"{self.device_id}-power-l1-w"
@computed_field # type: ignore[prop-decorator]
@property
def measurement_key_power_l2_w(self) -> str:
"""Measurement key for the L2 power the battery is charged or discharged with [W]."""
return f"{self.device_id}-power-l2-w"
@computed_field # type: ignore[prop-decorator]
@property
def measurement_key_power_l3_w(self) -> str:
"""Measurement key for the L3 power the battery is charged or discharged with [W]."""
return f"{self.device_id}-power-l3-w"
@computed_field # type: ignore[prop-decorator]
@property
def measurement_key_power_3_phase_sym_w(self) -> str:
"""Measurement key for the symmetric 3 phase power the battery is charged or discharged with [W]."""
return f"{self.device_id}-power-3-phase-sym-w"
@computed_field # type: ignore[prop-decorator]
@property
def measurement_keys(self) -> Optional[list[str]]:
"""Measurement keys for the battery stati that are measurements."""
keys: list[str] = [
self.measurement_key_soc_factor,
self.measurement_key_power_l1_w,
self.measurement_key_power_l2_w,
self.measurement_key_power_l3_w,
self.measurement_key_power_3_phase_sym_w,
]
return keys
class InverterCommonSettings(DevicesBaseSettings):
"""Inverter devices base settings."""
max_power_w: Optional[float] = Field(
default=None,
gt=0,
json_schema_extra={"description": "Maximum power [W].", "examples": [10000]},
)
battery_id: Optional[str] = Field(
default=None,
json_schema_extra={
"description": "ID of battery controlled by this inverter.",
"examples": [None, "battery1"],
},
)
ac_to_dc_efficiency: float = Field(
default=1.0,
ge=0,
le=1,
json_schema_extra={
"description": (
"Efficiency of AC to DC conversion for grid-to-battery AC charging (0-1). "
"Set to 0 to disable AC charging. Default 1.0 (no additional inverter loss)."
),
"examples": [0.95, 1.0, 0.0],
},
)
dc_to_ac_efficiency: float = Field(
default=1.0,
gt=0,
le=1,
json_schema_extra={
"description": (
"Efficiency of DC to AC conversion for battery discharging to AC load/grid (0-1). "
"Default 1.0 (no additional inverter loss)."
),
"examples": [0.95, 1.0],
},
)
max_ac_charge_power_w: Optional[float] = Field(
default=None,
ge=0,
json_schema_extra={
"description": (
"Maximum AC charging power in watts. "
"null means no additional limit. Set to 0 to disable AC charging."
),
"examples": [None, 0, 5000],
},
)
@computed_field # type: ignore[prop-decorator]
@property
def measurement_keys(self) -> Optional[list[str]]:
"""Measurement keys for the inverter stati that are measurements."""
keys: list[str] = []
return keys
class HomeApplianceCommonSettings(DevicesBaseSettings):
"""Home Appliance devices base settings."""
consumption_wh: int = Field(
gt=0, json_schema_extra={"description": "Energy consumption [Wh].", "examples": [2000]}
)
duration_h: int = Field(
gt=0,
le=24,
json_schema_extra={"description": "Usage duration in hours [0 ... 24].", "examples": [1]},
)
time_windows: Optional[TimeWindowSequence] = Field(
default=None,
json_schema_extra={
"description": "Sequence of allowed time windows. Defaults to optimization general time window.",
"examples": [
{
"windows": [
{"start_time": "10:00", "duration": "2 hours"},
],
},
],
},
)
@computed_field # type: ignore[prop-decorator]
@property
def measurement_keys(self) -> Optional[list[str]]:
"""Measurement keys for the home appliance stati that are measurements."""
keys: list[str] = []
return keys
class DevicesCommonSettings(SettingsBaseModel):
"""Base configuration for devices simulation settings."""
"""Configuration for all controllable devices in the simulation.
batteries: Optional[list[BatteriesCommonSettings]] = Field(
Every device collection is a ``dict[str, <Settings>]`` keyed by
``device_id``. This makes config paths stable regardless of
declaration order and lets each device settings class build its own
config path from ``self.device_id`` without needing an external index.
"""
# ---- Batteries ----
batteries: Optional[dict[str, BatteriesCommonSettings]] = Field(
default=None,
json_schema_extra={
"description": "List of battery devices",
"examples": [[{"device_id": "battery1", "capacity_wh": 8000}]],
"description": "Stationary battery storage devices, keyed by device_id.",
"examples": [{"bat0": {"device_id": "bat0", "capacity_wh": 8000, "ports": []}}],
"x-scope": [str(ConfigScope.GENETIC), str(ConfigScope.GENETIC0)],
},
)
max_batteries: Optional[int] = Field(
default=None,
ge=0,
json_schema_extra={
"description": "Maximum number of batteries that can be set",
"examples": [1, 2],
"description": "Maximum number of batteries allowed.",
"examples": [1],
"x-scope": [str(ConfigScope.GENETIC), str(ConfigScope.GENETIC0)],
},
)
electric_vehicles: Optional[list[BatteriesCommonSettings]] = Field(
# ---- Electric vehicles ----
electric_vehicles: Optional[dict[str, BatteriesCommonSettings]] = Field(
default=None,
json_schema_extra={
"description": "List of electric vehicle devices",
"examples": [[{"device_id": "battery1", "capacity_wh": 8000}]],
"description": "Electric vehicle battery packs, keyed by device_id.",
"examples": [{"ev0": {"device_id": "ev0", "capacity_wh": 60000, "ports": []}}],
"x-scope": [str(ConfigScope.GENETIC), str(ConfigScope.GENETIC0)],
},
)
max_electric_vehicles: Optional[int] = Field(
default=None,
ge=0,
json_schema_extra={
"description": "Maximum number of electric vehicles that can be set",
"examples": [1, 2],
"description": "Maximum number of EVs allowed.",
"examples": [1],
"x-scope": [str(ConfigScope.GENETIC), str(ConfigScope.GENETIC0)],
},
)
inverters: Optional[list[InverterCommonSettings]] = Field(
default=None, json_schema_extra={"description": "List of inverters", "examples": [[]]}
# ---- Inverters ----
inverters: Optional[dict[str, InverterCommonSettings]] = Field(
default=None,
json_schema_extra={
"description": "Inverter devices, keyed by device_id.",
"examples": [{}],
"x-scope": [str(ConfigScope.GENETIC), str(ConfigScope.GENETIC0)],
},
)
max_inverters: Optional[int] = Field(
default=None,
ge=0,
json_schema_extra={
"description": "Maximum number of inverters that can be set",
"examples": [1, 2],
"description": "Maximum number of inverters allowed.",
"examples": [1],
"x-scope": [str(ConfigScope.GENETIC), str(ConfigScope.GENETIC0)],
},
)
home_appliances: Optional[list[HomeApplianceCommonSettings]] = Field(
default=None, json_schema_extra={"description": "List of home appliances", "examples": [[]]}
# ---- Controllable home appliances ----
home_appliances: dict[str, HomeApplianceCommonSettings] = Field(
default_factory=dict,
json_schema_extra={
"description": "Shiftable home appliance devices, keyed by device_id.",
"examples": [
{
"dishwasher": {
"device_id": "dishwasher",
"consumption_wh": 1500,
"duration_h": 2.0, # required field
"ports": [{"bus_id": "bus_ac", "port_id": "p_ac", "direction": "sink"}],
},
},
],
"x-scope": [str(ConfigScope.GENETIC), str(ConfigScope.GENETIC0)],
},
)
max_home_appliances: Optional[int] = Field(
default=None,
ge=0,
json_schema_extra={
"description": "Maximum number of home_appliances that can be set",
"examples": [1, 2],
"description": "Maximum number of home appliances allowed.",
"examples": [3],
"x-scope": [str(ConfigScope.GENETIC), str(ConfigScope.GENETIC0)],
},
)
@field_validator(
"batteries", "electric_vehicles", "inverters", "home_appliances", mode="before"
)
@classmethod
def validate_device_ids(cls, value: Any) -> Any:
"""Keep map keys and device identities consistent without mutating callers."""
if not isinstance(value, dict):
return value
result = {}
for key, device in value.items():
if isinstance(device, dict):
device = dict(device)
device.setdefault("device_id", key)
device_id = device["device_id"]
else:
device_id = device.device_id
if device_id != key:
raise ValueError(f"device_id {device_id!r} must match map key {key!r}")
result[key] = device
return result
@computed_field # type: ignore[prop-decorator]
@property
def measurement_keys(self) -> Optional[list[str]]:
"""Return the measurement keys for the resource/ device stati that are measurements."""
def measurement_keys(self) -> list[str]:
"""All measurement keys across all configured devices."""
keys: list[str] = []
if self.max_batteries and self.batteries:
for battery in self.batteries:
keys.extend(battery.measurement_keys or [])
if self.max_electric_vehicles and self.electric_vehicles:
for electric_vehicle in self.electric_vehicles:
keys.extend(electric_vehicle.measurement_keys or [])
for device_dict in [
self.batteries,
self.electric_vehicles,
self.inverters,
self.home_appliances,
]:
for device in (device_dict or {}).values():
keys.extend(device.measurement_keys or [])
return keys