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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>
226 lines
8.7 KiB
Markdown
226 lines
8.7 KiB
Markdown
## Configuration for all controllable devices in the simulation
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Every device collection is a ``dict[str, <Settings>]`` keyed by
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``device_id``. This makes config paths stable regardless of
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declaration order and lets each device settings class build its own
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config path from ``self.device_id`` without needing an external index.
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<!-- pyml disable line-length -->
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:::{table} devices
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:widths: 10 20 10 5 5 30
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:align: left
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| Name | Environment Variable | Type | Read-Only | Default | Description |
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| ---- | -------------------- | ---- | --------- | ------- | ----------- |
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| batteries | `EOS_DEVICES__BATTERIES` | `dict[str, akkudoktoreos.devices.settings.batterysettings.BatteriesCommonSettings] | None` | `rw` | `None` | Stationary battery storage devices, keyed by device_id. |
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| electric_vehicles | `EOS_DEVICES__ELECTRIC_VEHICLES` | `dict[str, akkudoktoreos.devices.settings.batterysettings.BatteriesCommonSettings] | None` | `rw` | `None` | Electric vehicle battery packs, keyed by device_id. |
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| home_appliances | `EOS_DEVICES__HOME_APPLIANCES` | `dict[str, akkudoktoreos.devices.settings.homeappliancesettings.HomeApplianceCommonSettings]` | `rw` | `required` | Shiftable home appliance devices, keyed by device_id. |
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| inverters | `EOS_DEVICES__INVERTERS` | `dict[str, akkudoktoreos.devices.settings.invertersettings.InverterCommonSettings] | None` | `rw` | `None` | Inverter devices, keyed by device_id. |
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| max_batteries | `EOS_DEVICES__MAX_BATTERIES` | `int | None` | `rw` | `None` | Maximum number of batteries allowed. |
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| max_electric_vehicles | `EOS_DEVICES__MAX_ELECTRIC_VEHICLES` | `int | None` | `rw` | `None` | Maximum number of EVs allowed. |
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| max_home_appliances | `EOS_DEVICES__MAX_HOME_APPLIANCES` | `int | None` | `rw` | `None` | Maximum number of home appliances allowed. |
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| max_inverters | `EOS_DEVICES__MAX_INVERTERS` | `int | None` | `rw` | `None` | Maximum number of inverters allowed. |
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| measurement_keys | | `list[str]` | `ro` | `N/A` | All measurement keys across all configured devices. |
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:::
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<!-- pyml enable line-length -->
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<!-- pyml disable no-emphasis-as-heading -->
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**Example Input**
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<!-- pyml enable no-emphasis-as-heading -->
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<!-- pyml disable line-length -->
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```json
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{
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"devices": {
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"batteries": {
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"bat0": {
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"device_id": "bat0",
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"capacity_wh": 8000,
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"charging_efficiency": 0.88,
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"discharging_efficiency": 0.88,
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"levelized_cost_of_storage_amt_kwh": 0.0,
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"max_charge_power_w": 5000,
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"min_charge_power_w": 50,
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"charge_rates": [
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0.0,
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0.1,
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0.2,
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0.3,
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0.4,
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0.5,
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0.6,
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0.7,
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0.8,
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0.9,
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1.0
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],
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"min_soc_percentage": 0,
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"max_soc_percentage": 100
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}
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},
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"max_batteries": 1,
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"electric_vehicles": {
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"ev0": {
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"device_id": "ev0",
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"capacity_wh": 60000,
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"charging_efficiency": 0.88,
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"discharging_efficiency": 0.88,
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"levelized_cost_of_storage_amt_kwh": 0.0,
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"max_charge_power_w": 5000,
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"min_charge_power_w": 50,
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"charge_rates": [
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0.0,
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0.1,
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0.2,
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0.3,
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0.4,
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0.5,
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0.6,
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0.7,
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0.8,
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0.9,
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1.0
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],
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"min_soc_percentage": 0,
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"max_soc_percentage": 100
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}
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},
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"max_electric_vehicles": 1,
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"inverters": {},
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"max_inverters": 1,
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"home_appliances": {
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"dishwasher": {
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"device_id": "dishwasher",
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"consumption_wh": 1500,
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"duration_h": 2,
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"num_cycles": 1,
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"cycle_time_windows": null,
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"min_cycle_gap_h": 0,
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"cycles_completed_measurement_key": null
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}
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},
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"max_home_appliances": 3
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}
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}
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```
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<!-- pyml enable line-length -->
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<!-- pyml disable no-emphasis-as-heading -->
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**Example Output**
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<!-- pyml enable no-emphasis-as-heading -->
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<!-- pyml disable line-length -->
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```json
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{
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"devices": {
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"batteries": {
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"bat0": {
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"device_id": "bat0",
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"capacity_wh": 8000,
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"charging_efficiency": 0.88,
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"discharging_efficiency": 0.88,
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"levelized_cost_of_storage_amt_kwh": 0.0,
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"max_charge_power_w": 5000,
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"min_charge_power_w": 50,
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"charge_rates": [
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0.0,
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0.1,
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0.2,
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0.3,
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0.4,
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0.5,
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0.6,
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0.7,
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0.8,
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0.9,
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1.0
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],
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"min_soc_percentage": 0,
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"max_soc_percentage": 100,
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"measurement_key_soc_factor": "bat0-soc-factor",
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"measurement_key_power_l1_w": "bat0-power-l1-w",
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"measurement_key_power_l2_w": "bat0-power-l2-w",
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"measurement_key_power_l3_w": "bat0-power-l3-w",
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"measurement_key_power_3_phase_sym_w": "bat0-power-3-phase-sym-w",
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"measurement_keys": [
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"bat0-soc-factor",
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"bat0-power-l1-w",
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"bat0-power-l2-w",
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"bat0-power-l3-w",
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"bat0-power-3-phase-sym-w"
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]
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}
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},
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"max_batteries": 1,
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"electric_vehicles": {
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"ev0": {
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"device_id": "ev0",
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"capacity_wh": 60000,
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"charging_efficiency": 0.88,
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"discharging_efficiency": 0.88,
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"levelized_cost_of_storage_amt_kwh": 0.0,
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"max_charge_power_w": 5000,
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"min_charge_power_w": 50,
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"charge_rates": [
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0.0,
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0.1,
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0.2,
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0.3,
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0.4,
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0.5,
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0.6,
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0.7,
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0.8,
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0.9,
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1.0
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],
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"min_soc_percentage": 0,
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"max_soc_percentage": 100,
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"measurement_key_soc_factor": "ev0-soc-factor",
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"measurement_key_power_l1_w": "ev0-power-l1-w",
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"measurement_key_power_l2_w": "ev0-power-l2-w",
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"measurement_key_power_l3_w": "ev0-power-l3-w",
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"measurement_key_power_3_phase_sym_w": "ev0-power-3-phase-sym-w",
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"measurement_keys": [
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"ev0-soc-factor",
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"ev0-power-l1-w",
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"ev0-power-l2-w",
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"ev0-power-l3-w",
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"ev0-power-3-phase-sym-w"
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]
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}
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},
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"max_electric_vehicles": 1,
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"inverters": {},
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"max_inverters": 1,
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"home_appliances": {
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"dishwasher": {
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"device_id": "dishwasher",
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"consumption_wh": 1500,
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"duration_h": 2,
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"num_cycles": 1,
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"cycle_time_windows": null,
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"min_cycle_gap_h": 0,
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"cycles_completed_measurement_key": null,
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"effective_num_cycles": 1,
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"measurement_keys": []
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}
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},
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"max_home_appliances": 3,
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"measurement_keys": [
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"bat0-soc-factor",
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"bat0-power-l1-w",
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"bat0-power-l2-w",
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"bat0-power-l3-w",
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"bat0-power-3-phase-sym-w",
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"ev0-soc-factor",
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"ev0-power-l1-w",
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"ev0-power-l2-w",
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"ev0-power-l3-w",
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"ev0-power-3-phase-sym-w"
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]
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}
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}
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```
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<!-- pyml enable line-length -->
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