EOS/docs/akkudoktoreos/optimization.md
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Signed-off-by: Bobby Noelte <b0661n0e17e@gmail.com>
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% SPDX-License-Identifier: Apache-2.0

Optimization

Introduction

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.

Input Payload

Sample Request

{
    "ems": {
        "preis_euro_pro_wh_akku": 0.0007,
        "einspeiseverguetung_euro_pro_wh": 0.00007,
        "gesamtlast": [500, 500, ..., 500, 500],
        "pv_prognose_wh": [300, 0, 0, ..., 2160, 1840],
        "strompreis_euro_pro_wh": [0.0003784, 0.0003868, ..., 0.00034102, 0.00033709]
    },
    "pv_akku": {
        "capacity_wh": 12000,
        "charging_efficiency": 0.92,
        "discharging_efficiency": 0.92,
        "max_charge_power_w": 5700,
        "initial_soc_percentage": 66,
        "min_soc_percentage": 5,
        "max_soc_percentage": 100
    },
    "inverter": {
        "max_power_wh": 15500
    },
    "eauto": {
        "capacity_wh": 64000,
        "charging_efficiency": 0.88,
        "discharging_efficiency": 0.88,
        "max_charge_power_w": 11040,
        "initial_soc_percentage": 98,
        "min_soc_percentage": 60,
        "max_soc_percentage": 100
    },
    "temperature_forecast": [18.3, 18, ..., 20.16, 19.84],
    "start_solution": null
}

Input Parameters

Energy Management System (EMS)

Battery Cost (preis_euro_pro_wh_akku)

  • Unit: €/Wh
  • Purpose: Represents the residual value of energy stored in the battery
  • Impact: Lower values encourage battery depletion, higher values preserve charge at the end of the simulation.

Feed-in Tariff (einspeiseverguetung_euro_pro_wh)

  • Unit: €/Wh
  • Purpose: Compensation received for feeding excess energy back to the grid

Total Load Forecast (gesamtlast)

  • Unit: W
  • Time Range: 48 hours (00:00 today to 23:00 tomorrow)
  • Format: Array of hourly values
  • Note: Exclude optimizable loads (EV charging, battery charging, etc.)
Data Sources
  1. Standard Load Profile: GET /v1/prediction/list?key=load_mean for a standard load profile based on your yearly consumption.
  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.

PV Generation Forecast (pv_prognose_wh)

  • Unit: W
  • Time Range: 48 hours (00:00 today to 23:00 tomorrow)
  • Format: Array of hourly values
  • Data Source: GET /v1/prediction/series?key=pvforecast_ac_power

Electricity Price Forecast (strompreis_euro_pro_wh)

  • Unit: €/Wh
  • Time Range: 48 hours (00:00 today to 23:00 tomorrow)
  • Format: Array of hourly values
  • Data Source: GET /v1/prediction/list?key=elecprice_marketprice_wh

Verify prices against your local tariffs.

Battery Storage System

Configuration

  • capacity_wh: Total battery capacity in Wh
  • charging_efficiency: Charging efficiency (0-1)
  • discharging_efficiency: Discharging efficiency (0-1)
  • max_charge_power_w: Maximum charging power in W

State of Charge (SoC)

  • initial_soc_percentage: Current battery level (%)
  • min_soc_percentage: Minimum allowed SoC (%)
  • max_soc_percentage: Maximum allowed SoC (%)

Inverter

  • max_power_wh: Maximum inverter power in Wh

Electric Vehicle (EV)

  • capacity_wh: Battery capacity in Wh
  • charging_efficiency: Charging efficiency (0-1)
  • discharging_efficiency: Discharging efficiency (0-1)
  • max_charge_power_w: Maximum charging power in W
  • initial_soc_percentage: Current charge level (%)
  • min_soc_percentage: Minimum allowed SoC (%)
  • max_soc_percentage: Maximum allowed SoC (%)

Temperature Forecast

  • Unit: °C
  • Time Range: 48 hours (00:00 today to 23:00 tomorrow)
  • Format: Array of hourly values
  • Data Source: GET /v1/prediction/list?key=weather_temp_air

Output Format

Sample Response

{
    "ac_charge": [0.625, 0, ..., 0.75, 0],
    "dc_charge": [1, 1, ..., 1, 1],
    "discharge_allowed": [0, 0, 1, ..., 0, 0],
    "eautocharge_hours_float": [0.625, 0, ..., 0.75, 0],
    "result": {
        "Last_Wh_pro_Stunde": [...],
        "EAuto_SoC_pro_Stunde": [...],
        "Einnahmen_Euro_pro_Stunde": [...],
        "Gesamt_Verluste": 1514.96,
        "Gesamtbilanz_Euro": 2.51,
        "Gesamteinnahmen_Euro": 2.88,
        "Gesamtkosten_Euro": 5.39,
        "akku_soc_pro_stunde": [...]
    }
}

Output Parameters

Battery Control

  • ac_charge: Grid charging schedule (0-1)
  • dc_charge: DC charging schedule (0-1)
  • discharge_allowed: Discharge permission (0 or 1)

0 (no charge) 1 (charge with full load)

ac_charge multiplied by the maximum charge power of the battery results in the planned charging power.

EV Charging

  • eautocharge_hours_float: EV charging schedule (0-1)

Results

The result object contains detailed information about the optimization outcome. The length of the array is between 25 and 48 and starts at the current hour and ends at 23:00 tomorrow.

  • Last_Wh_pro_Stunde: Array of hourly load values in Wh

    • Shows the total energy consumption per hour
    • Includes household load, battery charging/discharging, and EV charging
  • EAuto_SoC_pro_Stunde: Array of hourly EV state of charge values (%)

    • Shows the projected EV battery level throughout the optimization period
  • Einnahmen_Euro_pro_Stunde: Array of hourly revenue values in Euro

  • Gesamt_Verluste: Total energy losses in Wh

  • Gesamtbilanz_Euro: Overall financial balance in Euro

  • Gesamteinnahmen_Euro: Total revenue in Euro

  • Gesamtkosten_Euro: Total costs in Euro

  • akku_soc_pro_stunde: Array of hourly battery state of charge values (%)

Timeframe overview

:alt: Timeframe Overview

Timeframe Overview