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Initial "optimize" documentation
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Dennis
Bobby Noelte
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docs/_static/optimization_timeframes-excalidraw.json
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@ -2,7 +2,177 @@
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# Optimization
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:::{admonition} Todo
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:class: note
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Describe optimization.
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:::
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## Introduction
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The `POST /optimize` API endpoint optimizes your energy management system based on various inputs including electricity prices, battery storage capacity, PV forecast, and temperature data.
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## Input Payload
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### Sample Request
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```json
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{
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"ems": {
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"preis_euro_pro_wh_akku": 0.0007,
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"einspeiseverguetung_euro_pro_wh": 0.00007,
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"gesamtlast": [500, 500, ..., 500, 500],
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"pv_prognose_wh": [300, 0, 0, ..., 2160, 1840],
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"strompreis_euro_pro_wh": [0.0003784, 0.0003868, ..., 0.00034102, 0.00033709]
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},
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"pv_akku": {
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"capacity_wh": 12000,
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"charging_efficiency": 0.92,
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"discharging_efficiency": 0.92,
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"max_charge_power_w": 5700,
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"initial_soc_percentage": 66,
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"min_soc_percentage": 5,
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"max_soc_percentage": 100
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},
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"inverter": {
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"max_power_wh": 15500
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},
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"eauto": {
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"capacity_wh": 64000,
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"charging_efficiency": 0.88,
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"discharging_efficiency": 0.88,
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"max_charge_power_w": 11040,
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"initial_soc_percentage": 98,
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"min_soc_percentage": 60,
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"max_soc_percentage": 100
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},
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"temperature_forecast": [18.3, 18, ..., 20.16, 19.84],
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"start_solution": null
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}
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```
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## Input Parameters
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### Energy Management System (EMS)
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#### Battery Cost (`preis_euro_pro_wh_akku`)
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- Unit: €/Wh
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- Purpose: Represents the residual value of energy stored in the battery
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- Impact: Lower values encourage battery depletion, higher values preserve charge at the end of the simulation.
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#### Feed-in Tariff (`einspeiseverguetung_euro_pro_wh`)
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- Unit: €/Wh
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- Purpose: Compensation received for feeding excess energy back to the grid
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#### Total Load Forecast (`gesamtlast`)
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- Unit: W
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- Time Range: 48 hours (00:00 today to 23:00 tomorrow)
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- Format: Array of hourly values
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- Note: Exclude optimizable loads (EV charging, battery charging, etc.)
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##### Data Sources:
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1. Standard Load Profile: `GET /v1/prediction/list?key=load_mean` for a standard load profile based on your yearly consumption.
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2. Adjusted Load Profile: `GET /v1/prediction/list?key=load_mean_adjusted` for a combination of a standard load profile based on your yearly consumption incl. data from last 48h.
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#### PV Generation Forecast (`pv_prognose_wh`)
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- Unit: W
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- Time Range: 48 hours (00:00 today to 23:00 tomorrow)
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- Format: Array of hourly values
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- Data Source: `GET /v1/prediction/series?key=pvforecast_ac_power`
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#### Electricity Price Forecast (`strompreis_euro_pro_wh`)
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- Unit: €/Wh
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- Time Range: 48 hours (00:00 today to 23:00 tomorrow)
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- Format: Array of hourly values
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- Data Source: `GET /v1/prediction/list?key=elecprice_marketprice_wh`
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Verify prices against your local tariffs.
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### Battery Storage System
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#### Configuration
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- `capacity_wh`: Total battery capacity in Wh
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- `charging_efficiency`: Charging efficiency (0-1)
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- `discharging_efficiency`: Discharging efficiency (0-1)
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- `max_charge_power_w`: Maximum charging power in W
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#### State of Charge (SoC)
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- `initial_soc_percentage`: Current battery level (%)
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- `min_soc_percentage`: Minimum allowed SoC (%)
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- `max_soc_percentage`: Maximum allowed SoC (%)
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### Inverter
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- `max_power_wh`: Maximum inverter power in Wh
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### Electric Vehicle (EV)
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- `capacity_wh`: Battery capacity in Wh
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- `charging_efficiency`: Charging efficiency (0-1)
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- `discharging_efficiency`: Discharging efficiency (0-1)
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- `max_charge_power_w`: Maximum charging power in W
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- `initial_soc_percentage`: Current charge level (%)
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- `min_soc_percentage`: Minimum allowed SoC (%)
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- `max_soc_percentage`: Maximum allowed SoC (%)
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### Temperature Forecast
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- Unit: °C
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- Time Range: 48 hours (00:00 today to 23:00 tomorrow)
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- Format: Array of hourly values
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- Data Source: `GET /v1/prediction/list?key=weather_temp_air`
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## Output Format
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### Sample Response
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```json
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{
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"ac_charge": [0.625, 0, ..., 0.75, 0],
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"dc_charge": [1, 1, ..., 1, 1],
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"discharge_allowed": [0, 0, 1, ..., 0, 0],
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"eautocharge_hours_float": [0.625, 0, ..., 0.75, 0],
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"result": {
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"Last_Wh_pro_Stunde": [...],
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"EAuto_SoC_pro_Stunde": [...],
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"Einnahmen_Euro_pro_Stunde": [...],
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"Gesamt_Verluste": 1514.96,
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"Gesamtbilanz_Euro": 2.51,
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"Gesamteinnahmen_Euro": 2.88,
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"Gesamtkosten_Euro": 5.39,
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"akku_soc_pro_stunde": [...]
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}
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}
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```
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### Output Parameters
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#### Battery Control
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- `ac_charge`: Grid charging schedule (0-1)
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- `dc_charge`: DC charging schedule (0-1)
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- `discharge_allowed`: Discharge permission (0 or 1)
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0 (no charge)
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1 (charge with full load)
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`ac_charge` multiplied by the maximum charge power of the battery results in the planned charging power.
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#### EV Charging
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- `eautocharge_hours_float`: EV charging schedule (0-1)
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#### Results
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The `result` object contains detailed information about the optimization outcome.
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The length of the array is between 25 and 48 and starts at the current hour and ends at 23:00 tomorrow.
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- `Last_Wh_pro_Stunde`: Array of hourly load values in Wh
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- Shows the total energy consumption per hour
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- Includes household load, battery charging/discharging, and EV charging
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- `EAuto_SoC_pro_Stunde`: Array of hourly EV state of charge values (%)
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- Shows the projected EV battery level throughout the optimization period
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- `Einnahmen_Euro_pro_Stunde`: Array of hourly revenue values in Euro
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- `Gesamt_Verluste`: Total energy losses in Wh
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- `Gesamtbilanz_Euro`: Overall financial balance in Euro
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- `Gesamteinnahmen_Euro`: Total revenue in Euro
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- `Gesamtkosten_Euro`: Total costs in Euro
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- `akku_soc_pro_stunde`: Array of hourly battery state of charge values (%)
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## Timeframe overview
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<a href="../_static/optimization_timeframes.png" target="_blank">
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<img src="../_static/optimization_timeframes.png" alt="EOS Price in euro per watt hour in battery" width="300">
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</a>
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