Published:
September 4, 2023
Last updated:
September 11, 2023

Putting electricity time of use tariff to use

Electricity prices vary over time. One of the biggest factors affecting this is the share of renewables in the power mix. The higher the share, the lower the price. In fact, an analysis of wholesale electricity prices and the share of renewables in Germany in the first seven months in 2023 showed that the power price dropped by 1.59 €/MWh for each percentage point of clean electricity. Simply speaking: the cleaner the electricity, the lower the price.

Time of use tariffs pass on this price signal to consumers, providing a strong incentive to shift consumption to cheaper and cleaner hours and feed into the grid when clean electricity is scarce.

But manually responding to power prices would be quite a cumbersome task – after all, you would not want to run to your EV and plug it in at 3am just to save some euros. And that’s why we built our Tariff Timer Module, which allows all XENON customers to offer an energy management system that acts on current market prices to keep electricity costs to a minimum.

In this post, we explain how the optimization works, how we make decision-making transparent to the user, how we enable users to input their specific tariff and what features we will add over the coming months.

Optimization: intelligently (dis)charging batteries and EVs 

With this release, our Tariff Timer considers time-varying prices, load forecasts and production forecasts. It charges/discharges batteries and EVs accordingly to minimize electricity costs. Forecasts are system-specific. For each system (i.e. household) we consider historic consumption and production as well as third-party data on solar radiation. Forecasts are updated every 30 minutes to reevaluate and adapt the schedule. In first simulations, we found that EV owners may save up to €213 per year by shifting charging to cheaper times – depending on their country.

We consider four cases where it makes sense to deviate from a simple self-sufficiency optimization where the battery is discharged when demand exceeds production and charged when production exceeds demand.

Case 1: Don’t discharge the battery, keep power for later

Action:  The battery is not discharged to cover household consumption and the grid is used instead. 

Reason: This is done when the import price is low but will increase in the future. The user effectively saves the battery’s power for later, more expensive hours. Thereby, grid supply is reduced during peak price hours.

Example: The import price stands at 8 ct/kWh at 4 pm. In the evening hours (7 - 9 pm) the price rises back to 30 ct/kWh. By drawing power from the grid at 4 pm and using the battery’s energy to cover electricity demand during peak hours later, the user saves 22 ct/kWh.

Case 2: Charge battery from the grid

Action:  The battery is charged directly from the grid. 

Reason: This is done when prices are low but will increase in the next hours. Effectively, the user locks in cheap electricity prices and reduces grid supply during expensive hours.

Example: The retail price is 10 ct/kWh at 4 am. In the morning hours (7 - 9 am) the price rises back to 30 ct/kWh. By charging the battery at 4 am and using this energy to cover electricity demand the user capitalizes on the spread of 22 ct/kWh.

*Please note, that charging batteries from the grid is currently not allowed in all countries (🇩🇪👀).

Case 3: Inject PV surplus into grid, instead of battery charging

Action: Solar surplus feed-in is aligned with feed-in compensation.

Reason: Feed-in compensation can also vary over time. On days where solar production is likely to exceed consumption and battery capacity (i.e. the system will feed into the grid at some point), feed-in is aligned to take advantage of the highest compensation.

Example: Feed-in compensation is at 15 ct/kWh at 9am. At noon it drops to 6 ct/kWh. If all surplus power was used to charge the battery it would be full at noon. By feeding into the grid in the morning instead of noon, the user gains 9 ct for every kWh.

Case 4: Charge EV with full power

Action: The EV is charged with full power when electricity is cheapest.

Reason: Well… you pay less for charging.

Example: The EV is plugged in at 8 pm and remains parked until 8 am. Charging is delayed until electricity is cheapest.

Bring your own prices

Wholesale prices i.e. day-ahead prices are usually the main determinants of dynamic retail prices. And wholesale prices are readily available. However, each electricity provider may apply their own conversion and that’s why we enable each partner to bring their own pricing logic.

We determine the relevant pricing zone based on the user’s address and the user then inputs the offset, tax, grid fees and margin their electricity provider charges in addition to the wholesale price.

Further down the road

This is our first release of the Tariff Timer available to all XENON users – but certainly not our last. Over the coming months will we add more features:

  • API for prices: Partners can then enter their own pricing schedules programmatically via our API by simply providing a list of intervals and corresponding prices.
  • Heat pump support: Currently, heat pumps are not considered as flexible loads. In the future, we also aim to control them in response to power prices without compromising user comfort.
  • Transparent savings: With the first release we only detail the number of decisions that overruled the self-sufficiency optimization. In an upcoming release we will add further insights into the savings realized by the Tariff Timer.

Get started with your own smart HEMS

Are you planning to launch your own smart HEMS? Reach out to book a demo, experience XENON yourself and discuss how we can get your own HEMS off the ground.

Get the report!
Time of Use Tariffs: Time is Money
Time of Use (ToU) tariffs incentivize consumers to shift their loads to off peak periods and thus reduce the strain on the grid and increase the share of renewables.
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