Energy dashboard and ESG practices

Why learn this: replace “it feels expensive” with evidence

When a utility bill arrives, the usual reaction is “Why is it so high again?”—and the discussion ends there. The bill provides a total, but it does not tell you which appliance contributed to it.

The Energy Dashboard addresses that problem. This built-in Home Assistant dashboard charts how many kilowatt-hours you used today, daily consumption across the month, and which devices used the most energy. It can also apply a tariff to estimate cost.

Here are some practical examples:

• At home: You suspect an old refrigerator uses too much energy but have no evidence. Monitor it with a suitable smart plug; after two weeks, its steady daily consumption will show whether replacement may be worthwhile.
• In a room: A dehumidifier is left on all day. Its daily energy chart immediately reveals an unusual increase of perhaps 3 kWh.
• In an office pantry: A hot-water dispenser keeps water warm 24 hours a day. It may draw only a few hundred watts, yet consume more over a month than a copier. Only cumulative data exposes this kind of continuous, moderate load.
• In an ESG report: A small office can write, “We installed energy-monitoring plugs and limited pantry water heating to business hours, reducing monthly consumption by X kWh.” That carries far more weight than “We reminded staff to switch off the lights.”

This chapter makes extensive use of the helpers introduced in Appendix B and the entity IDs and naming practices covered in Chapter 4. For adding devices to Home Assistant, see Chapter 11. If you are not yet sure what a sensor is, first review Chapter 12, specifically the sensor section.

First distinguish power (W) from energy (kWh)

This is the chapter’s most important—and most commonly confused—concept. Remember it this way: power is like speed; energy is like distance.

Your electricity provider bills for kilowatt-hours (1 kWh), not watts. For example:

• A 1000 W electric heater running for 1 hour uses 1 kWh.
• A 100 W hot-water dispenser running for 24 hours uses 2.4 kWh—more than the heater in the example above.

Many inexpensive smart plugs report only current power in watts, not cumulative energy in kilowatt-hours. The Energy Dashboard primarily needs energy data: its daily consumption, monthly cost, and similar charts all derive from kWh totals. This is why a plug can provide power monitoring but still be absent from the dashboard’s selectors.

What makes a sensor eligible for the Energy Dashboard?

The Energy Dashboard does not accept every sensor. It filters the list and shows only entities with compatible attributes. Check all three of the following:

How the three state classes differ

How to inspect a sensor’s attributes

Open Settings → Tools → States, search for your sensor, and inspect the attributes shown alongside it. The same area includes a Statistics tab listing entities with long-term statistics. If an entity’s statistics are invalid, a “Fix issue” link appears there.

Where energy data comes from: five sources

Without hardware, there is no measurement. The following options progress from simple to more involved.

Smart plugs

Whole-property metering

To measure the whole property rather than one appliance, you need monitoring at the distribution board. A clamp-on CT sensor fits around a main conductor and connects to a module that reports to Home Assistant, such as a compatible Shelly device or a custom ESPHome system.

Solar generation and battery storage

Most solar inverter brands provide an API or local interface, and Home Assistant has integrations that can read current generation power and cumulative energy generated. Battery systems generally provide separate cumulative figures for charging and discharging. In the Energy Dashboard settings, solar and batteries are separate sections that require different sensors.

Hands on: enable the Energy Dashboard

Assume that you already have a plug reporting cumulative energy—for example, the plug monitoring a living-room air conditioner. Follow these steps to turn its readings into charts.

1. Confirm that the sensor is eligible

   Open Settings → Tools → States and search for the plug’s sensors. Select the one measured in kWh whose value only increases, not the one measured in W. Confirm that it has device_class: energy, state_class: total_increasing, and unit_of_measurement: kWh. If all three are correct, continue.

2. Open the Energy settings

   Go to Settings → Dashboards → Energy → Edit dashboard. You can configure six source types: Electricity grid, Solar, Battery storage, Gas, Water, and Individual devices.

   Version note: Beginning in March 2026, this settings page is divided into Electricity, Gas, and Water tabs, with the six source types distributed among them instead of appearing on one long page. Older versions show everything together. Do not worry if your layout differs; the settings themselves are unchanged.

3. Add grid consumption first

   Under Electricity grid, select “Add consumption,” then choose your sensor from the drop-down list. If your sensor does not appear, an incorrect attribute is the cause about 80% of the time. Review the three fields under Eligible sensors.

4. Configure the tariff, or skip it for now

   After you add a sensor, the same dialog asks how to calculate cost. If you initially want only kWh totals, select no cost tracking; you can return and configure it at any time. See Tariffs and costs for the full procedure.

5. Add an appliance under Individual devices

   To see what proportion of total use comes from an air conditioner, retain the whole-property meter under Electricity grid and add the air conditioner’s energy sensor under Individual devices. The dashboard will then compare consumption across devices.

6. Save, then let statistics accumulate

   After setup, an Energy item appears in the sidebar. An empty dashboard immediately after setup is normal. Statistics accumulate hourly, so wait at least one or two hours for the first bar and a full day for a useful daily chart.

7. Return the next day to adjust the layout

   Once data is available, select “Customize cards” from the Energy Dashboard toolbar. Expand the Overview, Electricity, Gas, Water, and Now sections, then use the switches to control which cards appear. Disable sections you do not use to keep the display clear.

   The Energy Dashboard’s second tab was also renamed from “Energy” to “Electricity” in March 2026. Because the dashboard covers electricity, gas, and water, the previous label was easy to misinterpret.

Only have watts? Use a Riemann sum to calculate kWh

This is a common situation: a plug provides only sensor.xxx_power, measured in W, and no cumulative kWh sensor. The Energy Dashboard cannot use that sensor as cumulative energy.

The solution is Home Assistant’s built-in Integral (Riemann sum integral) helper. It repeatedly reads the power sensor and adds “watts × elapsed time” for each interval, producing a new cumulative energy sensor.

Create it in the interface (recommended)

1. Open the Helpers page

   Go to Settings → Devices & services → Helpers tab → Create helper.

2. Select Integral

   The list is long, so typing integ in the search box is quickest. A localised interface may use a translated label such as “Integral sensor.”

3. Select the input sensor

   For Input sensor, select the power sensor measured in W. Give the helper a clear name, such as “Living-room AC energy.”

4. Set the metric prefix and integration time

   These two settings are critical. Set Metric prefix to k and Integration time to h (hours). W × h ÷ 1000 = kWh, so these settings produce kWh. If the prefix is none, the result is Wh and its numeric value is 1000 times the kWh value.

5. Keep the default integration method

   Method offers Trapezoidal, Left, and Right. Trapezoidal is the default and, according to the official guidance, currently gives the best result when the source updates frequently. Do not change it unless you understand how the source reports its values.

6. Set Max sub-interval

   Max sub-interval is intended for devices that do not report again when their value remains unchanged. If you set a value such as 60 seconds, integration continues as time passes even without a new source update. A value of 0 disables this behaviour. Consider setting an interval for loads such as air conditioners and dehumidifiers that may hold a steady power level for long periods.

Create it in YAML

If you prefer configuration files, the equivalent YAML is:

sensor:
  - platform: integration
    source: sensor.living_room_ac_power
    name: Living-room AC energy
    unit_prefix: k
    unit_time: h
    method: trapezoidal
    max_sub_interval: "00:01:00"
    round: 3

source is the required source entity; unit_prefix is the metric prefix; unit_time is the time unit; method selects the integration method; round sets the number of decimal places; and max_sub_interval is the forced update interval described above.

Utility Meter: divide cumulative totals into daily, monthly, or quarterly cycles

After integration, you have a total that continually increases from the installation date. What you usually want to know, however, is how many kilowatt-hours you used today or whether this month is higher or lower than last month. The Utility Meter helper solves this problem by acting like a counter that resets automatically.

Create it in the interface

1. Open the Helpers page again

   Go to Settings → Devices & services → Helpers tab → Create helper → Utility Meter.

2. Select the input sensor

   Select the kWh sensor created by the Integral helper, or a cumulative energy sensor provided directly by your hardware.

3. Select a reset cycle

   Meter reset cycle can be every 15 minutes, hourly, daily, weekly, monthly, bimonthly, quarterly, or yearly. Consider creating three separate meters—daily, monthly, and yearly—and name each one clearly.

4. Enable Periodically resetting when appropriate

   If the source sensor can reset—for example, when a smart plug loses power—ensure that Periodically resetting is enabled so Utility Meter handles the decrease correctly. This option is enabled by default.

5. Set an offset if needed

   Meter reset offset moves the beginning of the cycle later. For example, if your electricity bill closes on the 5th of each month, set the monthly cycle’s offset to 4 days so the Home Assistant period aligns with the bill.

YAML configuration

utility_meter:
  ac_daily:
    source: sensor.living_room_ac_energy
    name: Living-room AC energy today
    cycle: daily
  ac_monthly:
    source: sensor.living_room_ac_energy
    name: Living-room AC energy this month
    cycle: monthly
  ac_yearly:
    source: sensor.living_room_ac_energy
    name: Living-room AC energy this year
    cycle: yearly

Available configuration keys include source, name, unique_id, cycle, offset, cron, delta_values, net_consumption, tariffs, periodically_resetting, and always_available. delta_values defaults to false, meaning the source reports an absolute reading rather than increments. net_consumption defaults to false, meaning only forward consumption is counted. periodically_resetting defaults to true.

Utility Meter also provides actions

It provides two actions (formerly called services):

These sensors are restored across restarts. Restarting Home Assistant will not erase a monthly total.

Tariffs and cost tracking

Once you have kWh totals, applying a tariff turns them into money. Cost can be more persuasive than energy alone: telling a manager that standby loads incur an annual cost of approximately 8000 in your local currency may be more effective than saying they use 200 kWh, provided you document the tariff and calculation period.

Three ways to calculate cost

After you add a consumption source in the Energy settings, Home Assistant asks how you want to track cost. The options broadly fall into three categories:

How local tariffs affect cost tracking

Two common features of residential tariffs can make a single fixed price imprecise:

• Tiered rates: The unit price may rise above specified consumption thresholds, so your average rate increases as usage grows.
• Seasonal rates: Some utilities charge different rates during defined seasons.

Configure a time-of-use tariff

If your plan charges different peak and off-peak prices, use Utility Meter’s Tariffs feature:

utility_meter:
  home_daily:
    source: sensor.home_energy
    name: Household energy today
    cycle: daily
    tariffs:
      - peak
      - offpeak
  home_monthly:
    source: sensor.home_energy
    name: Household energy this month
    cycle: monthly
    tariffs:
      - peak
      - offpeak

This creates four sensors—sensor.home_daily_peak, sensor.home_daily_offpeak, sensor.home_monthly_peak, and sensor.home_monthly_offpeak—plus two Select entities, select.home_daily and select.home_monthly, for choosing the active tariff period.

Next, create an automation that changes the Select entity at the tariff transition:

alias: Switch to the peak tariff
triggers:
  - trigger: time
    at: "16:00:00"
conditions:
  - condition: time
    weekday:
      - mon
      - tue
      - wed
      - thu
      - fri
actions:
  - action: select.select_option
    target:
      entity_id: select.home_daily
    data:
      option: peak
mode: single

Create a corresponding automation to switch back to off-peak. Use the exact transition times, weekday and holiday rules, and seasonal conditions specified by your tariff.

Gas and water: the other parts of an ESG inventory

If your only aim is to reduce the electricity bill, you may already have enough. A comprehensive ESG or sustainability inventory, however, should also account for gas and water.

The Energy Dashboard has separate Gas and Water sections. Their setup follows the same principle as electricity: provide a cumulative sensor with device_class set to gas or water, state_class set to total_increasing or total, and a supported volume unit. You can also apply a local-currency unit price after adding it.

The difficult part is hardware. Many residential gas and water meters do not provide a ready-made smart interface. The official documentation describes several common approaches:

ESG reporting: turn data into a defensible account

Data alone does not persuade people; comparison does. This section explains how to turn dashboard charts into a coherent report with a beginning, an intervention, and a result.

Step 1: Establish a baseline

Change nothing at first. Let the system collect a complete period—at least two weeks, and preferably one month. These figures form your baseline for every later comparison.

Step 2: Identify the largest loads

You do not need advanced analysis. Start with three views:

Step 3: Apply common office improvements

• Schedule pantry water heating: Use the automations from Chapter 8 so water heating operates only during business hours. This eliminates two to three full days of keep-warm energy over weekends and public-holiday periods.
• Switch equipment off after work: Connect copiers, monitors, and desktop equipment to suitable smart plugs and switch them off together at 10 p.m.
• Assess air-conditioner setpoints: Measure before changing anything. Compare air-conditioning energy with outdoor temperature to estimate how much raising the setpoint by one degree saves.
• Notify on abnormal demand: Create an automation that sends a notification when total power exceeds a chosen threshold outside business hours; see Chapter 7. This often catches equipment that somebody forgot to switch off.

Step 4: Write the report

A useful energy-saving report needs only the following sections; it does not need to read like an academic paper:

1. Measurement method

   State which circuits or devices you measured, what equipment you used, and the start and end dates. Be candid about anything not measured—for example, “Lighting circuit not included.” This increases credibility.

2. Baseline data

   Give pre-improvement monthly consumption, the daily average, and standby base load. Include figures from the Energy Dashboard’s monthly view.

3. Measures taken

   List each measure separately and state what changed and when it began. If an automation is involved, include its trigger conditions as evidence of implementation.

4. Post-improvement data and comparison

   Compare energy use over periods of equal length. Report both the absolute change in kWh and the percentage change, then add a local-currency estimate using the documented tariff.

5. Confounding factors

   Be honest about external influences: “This period was outside the cooling season and temperatures were lower, so seasonal conditions explain part of the reduction.” A report that includes this caveat is far more credible than one that appears perfect.

Advanced: device rankings and solar self-consumption

Rank consumption by device

Add each smart plug’s kWh sensor to Individual devices in the Energy settings. The dashboard will automatically rank the devices by energy use.

If a circuit’s main meter and its downstream devices are all listed, consumption can be double-counted because the main meter already includes the devices below it. Home Assistant provides an “upstream device” setting to represent this hierarchy.

Current power distribution

The newer Distribution card shows the proportional distribution among several entities as a horizontal bar, with an interactive legend. Select or clear legend entries and the percentages recalculate immediately. Add a set of power sensors to see which circuit or appliance is drawing power right now. This is particularly useful for identifying the cause of a sudden load increase.

The Energy Dashboard’s Now view also continues to expand. Badges at the top show current electric power, gas flow, and water flow. Water has its own Sankey chart, similar to the electricity chart, showing where water is going. For a quick picture of what is running now, this view is faster than assembling custom cards.

Solar self-consumption rate

With solar, one useful indicator is how much generated energy you consume on site and how much you export to the grid.

Once solar sources are configured, the Energy Dashboard shows generation in relation to grid import and export. For a specific percentage, create a Template sensor based on “(total generation − grid export) ÷ total generation”:

template:
  - sensor:
      - name: "Solar self-consumption ratio"
        unique_id: solar_self_consumption_ratio
        unit_of_measurement: "%"
        state_class: measurement
        availability: >
          {{ is_number(states('sensor.solar_production_monthly'))
             and is_number(states('sensor.grid_export_monthly'))
             and states('sensor.solar_production_monthly') | float(0) > 0 }}
        state: >
          {% set gen = states('sensor.solar_production_monthly') | float(0) %}
          {% set exp = states('sensor.grid_export_monthly') | float(0) %}
          {{ ((gen - exp) / gen * 100) | round(1) }}

Replace sensor.solar_production_monthly and sensor.grid_export_monthly with your own monthly Utility Meter sensors. The availability block prevents an invalid result while either source is unavailable or generation is zero.

How long is data retained?

Many users worry about database growth. First distinguish these two kinds of data:

Troubleshooting

1. My sensor is missing from the Energy settings selector

   In most cases, its attributes are incompatible. Open Settings → Tools → States (Developer tools in older versions) and check that device_class is energy (or gas / water), state_class is total_increasing or total, and unit_of_measurement is supported. Capitalisation must be exact: kWh is valid, but KWH and kwh are not. You may also have selected the power sensor in W rather than the energy sensor in kWh; their names often differ by only one word.

2. One day shows several thousand kilowatt-hours

   A common cause is a source sensor that resets to zero but is treated as continuously cumulative, or a device that resets while using state_class total. Home Assistant may then count the jump from 0 back to a large reading as one enormous increase.
   Fix the cause: Change the sensor’s state_class to total_increasing. If it feeds Utility Meter, ensure that Periodically resetting is enabled.
   Repair the existing statistic: Open Settings → Tools → Statistics, find the entity, locate the bad data point by date and time, and correct it to a reasonable value. This is Home Assistant’s official interface for repairing statistics; a “Fix issue” link also appears beside an entity when Home Assistant detects a problem.

3. The dashboard remains empty after setup

   First, make sure you have waited long enough. Statistics are written hourly, so a newly configured dashboard will be empty; allow at least one or two hours. Next, confirm that Energy appears in the sidebar. If not, check configuration.yaml to see whether default_config: was removed. Finally, check whether the source sensor is changing. If it remains unavailable or unknown, the problem is the device connection, not the dashboard.

4. Repairs reports “state class is incompatible with device class”

   The most common invalid combination is device_class: power with total_increasing. Power is instantaneous and must use measurement. If an integration provides the sensor, report the problem to its developer or the device firmware vendor. If it is your own Template sensor, correct the YAML directly.

5. The integrated value is 1000 times too large or 1000 times too small

   The metric prefix (unit_prefix) and time unit (unit_time) are not paired correctly. To integrate W into kWh, use prefix k and time h. Leaving the prefix empty produces Wh. If the settings are wrong, delete and recreate the helper; correcting them does not retroactively repair previously accumulated data.

6. The appliance is running, but the Integral sensor is not changing

   The source power sensor may not report again while its value remains unchanged. Integration advances only when it receives a new sample. Open the Integral helper’s settings and give Max sub-interval a value such as 60 seconds, forcing the calculation to advance with time.

7. Utility Meter’s first month looks wrong

   This is expected: the official documentation states that the first cycle is necessarily incomplete. Wait for the next complete cycle before evaluating the result, and exclude the entire first cycle from reports.

8. Cost always shows 0

   Check that you actually selected a cost-tracking method in the Energy settings; the default is no cost tracking. If you selected an entity for the current unit price, confirm that its value is valid. A value of unknown cannot produce a cost. Cost statistics, like energy statistics, also take up to an hour to produce their first entry.

FAQ