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Load Modeling

The Load device composes a Node (power sink only) with an implicit PowerConnection to model power consumption based on forecast data.

Model Elements Created

graph LR
    subgraph "Device"
        SS["Node<br/>(is_source=false, is_sink=true)"]
        Conn["PowerConnection<br/>{name}:connection<br/>(fixed_power=true)"]
    end

    Node[Connection Target]


    Conn -->|linked via| SS
    Node -->|connects to| Conn
Model Element Name Parameters From Configuration
Node {name} is_source=false, is_sink=true
PowerConnection {name}:connection forecast as fixed power requirement

Devices Created

Load creates 1 device in Home Assistant:

Device Name Created When Purpose
Primary {name} Always Load consumption tracking

Parameter Mapping

The adapter transforms user configuration into model parameters:

User Configuration Model Element Model Parameter Notes
forecast PowerConnection max_power_target_source Required consumption at each time
connection PowerConnection source Node to connect from
— PowerConnection fixed_power=true Consumption must equal forecast
— Node is_source=false Load cannot provide power
— Node is_sink=true Load consumes power

Sensors Created

Load Device

Sensor Unit Update Description
power kW Real-time Power consumed by load
power_possible kW Real-time Maximum possible load (forecast)
forecast_limit_price $/kW Real-time Marginal cost of serving this load

See Load Configuration for detailed sensor and configuration documentation.

Configuration Examples

Variable Load (Forecast)

Field Value
Name House Load
Forecast sensor.home_power_forecast
Connection Home Bus

Constant Load

Field Value
Name Base Load
Forecast 2.5
Connection Home Bus

Typical Use Cases

Whole-House Consumption: Use historical data or forecasting services to predict total home power consumption. Enables optimizer to time battery discharge and grid import optimally.

Constant Base Load: Model always-on consumption (refrigerator, networking equipment) with a fixed power value.

Scheduled Loads: Model predictable loads like pool pumps, HVAC, or EV charging with time-varying forecasts.

Physical Interpretation

Load represents power consumption that must be satisfied by the system—either from grid, battery discharge, or solar generation.

Configuration Guidelines

  • Forecast Accuracy: Critical for optimization quality. Underestimating causes real system to import more than planned. Overestimating may cause infeasibility. See Forecasts and Sensors.
  • Constant vs Variable: Use constant values for stable always-on loads. Use forecast sensors for time-varying consumption patterns.
  • Multiple Loads: Create separate Load elements for different consumption categories (base load, HVAC, EV charging) to track them independently.
  • Fixed Power: Loads are NOT controllable—they represent consumption that will occur regardless of optimization decisions. The optimizer determines how to supply the power, not whether to supply it.

Next Steps