home-assistant.io/source/_integrations/integration.markdown

title, description, ha_category, ha_release, ha_iot_class, ha_quality_scale, ha_codeowners, ha_domain, ha_config_flow, ha_platforms, ha_integration_type

title	description	ha_category	ha_release	ha_iot_class	ha_quality_scale	ha_codeowners	ha_domain	ha_config_flow	ha_platforms	ha_integration_type
Integration - Riemann sum integral	Instructions on how to integrate Integration Sensor into Home Assistant.	Energy Helper Sensor Utility	0.87	Local Push	internal	@dgomes	integration	true	sensor	helper

This integrations provides the Riemann sum of the values provided by a source sensor. The Riemann sum is an approximation of an integral by a finite sum.

The integration sensors are updated upon changes of the source. Fast sampling source sensors provide more accurate results. In this implementation, the default is the Trapezoidal method, but Left and Right methods can optionally be used.

{% include integrations/config_flow.md %} {% configuration_basic %} Name: description: The name the sensor should have. You can change it again later. Input sensor: description: The entity providing numeric readings to integrate. Integral method: description: Riemann sum method to be used. Precision: description: Round the calculated integration value to at most N decimal places. Metric prefix: description: Metric unit to prefix the integration result. Integration time: description: SI unit of time to integrate over. {% endconfiguration_basic %}

YAML configuration

Alternatively, this integration can be configured and set up manually via YAML as well. To enable the Integration sensor in your installation, add the following to your configuration.yaml file:

# Example configuration.yaml entry
sensor:
  - platform: integration
    source: sensor.current_power

{% configuration %} source: description: The entity ID of the sensor providing numeric readings. required: true type: string name: description: Name to use in the frontend. required: false default: source entity ID integral type: string unique_id: description: An ID that uniquely identifies the integration sensor. Set this to a unique value to allow customization through the UI. required: false type: string round: description: Round the calculated integration value to at most N decimal places. required: false default: 3 type: integer unit_prefix: description: "Metric unit to prefix the integration result. Available units are k, M, G and T." required: false default: None type: string unit_time: description: "SI unit of time to integrate over. Available units are s, min, h and d." required: false default: h type: string method: description: "Riemann sum method to be used. Available methods are trapezoidal, left and right." required: false type: string default: trapezoidal {% endconfiguration %}

In case you expect that your source sensor will provide several subsequent values that are equal, you should opt for the left method to get accurate readings.

The unit of source together with unit_prefix and unit_time is used to generate a unit for the integral product (e.g. a source in W with prefix k and time h would result in kWh). Note that unit_prefix and unit_time are also relevant to the Riemann sum calculation.

Integration method

Riemann Sum is a approximation of an integral by a finite sum and is therefore intrinsically inaccurate, nonetheless, depending on the method used, values can be more or less accurate.

Regardless of the method used the integration will be more accurate if the source updates more often. If your source is not updated, neither will the Riemann Sum sensor, as all this integration does is calculate the next step in the event of a source update.

Trapezoidal

The trapezoidal method follows the Trapezoidal rule. This method is the most accurate of the currently implemented methods, if the source updates often, since it better fits the curve of the intrinsic source.

Left

The left method follows the Left rule. The method underestimates the intrinsic source, but is extremely accurate at estimating rectangular functions which are very stable for long periods of time and change very rapidly (e.g. such as the power function of a resistive load can jump instantly to a given value and stay at the same value for hours). If your source keeps its state for long periods of time, this method is preferable to the trapezoidal.

Right

The right method follows the Right rule. The method is similar to the left method, but overestimates the intrinsic source. Again it is only appropriate to be used with rectangular functions.

Energy

An integration sensor is quite useful in energy billing scenarios since energy is generally billed in kWh and many sensors provide power in W (Watts).

If you have a sensor that provides you with power readings in Watts (uses W as unit_of_measurement, device_class of power), then you can use the integration sensor to track how much energy is being spent. Take the next manual YAML configuration as an example:

sensor:
  - platform: integration
    source: sensor.current_power
    name: energy_spent
    unit_prefix: k
    round: 2

This configuration will provide you with sensor.energy_spent which will have your energy in kWh, as a device_class of energy.