Time-of-use tariffs mean end customers’ electricity prices are not fixed, but vary across time. ToU tariffs can reduce peak power demand by 10% on average. This data-file tracks the share of customers with time-of-use tariffs, by region, and then focuses in on interesting countries.
Time-of-use tariffs could greatly reduce the need for capacity growth in global power markets, as they tend to reduce demand by 10% on average at peak times (chart below), and potentially up to 20-50%, at households with electric vehicles and/or heat pumps. ToU tariffs also help to absorb solar and wind.
Dynamic or variable tariffs, in our definition, mean that pricing is split into bands. For example, pricing might be subject to a peak rate from 4-9pm and lowest from midnight to 6am.
Real-time pricing, in our definition, means that pricing varies hour-by-hour, or potentially even more frequently in regions with more granular wholesale power markets. The most advanced pilots, run by Ausgrid in South Australia, update their pricing every 5-minutes.
Looking globally, we estimate that time-of-use tariffs apply to 9% of power consumers globally in 2025, including 35% in the developed world and less than 5% in the emerging world. It will be interesting to update this chart in the future, and see how the numbers evolve.
Europe is the leader in time-of-use tariffs, especially in the Nord Pool region around Northern Europe. In Norway, for example, effectively all customers are on variable tariffs, and 70-90% are on real-time tariffs.
EIA 861 data, which we have tabulated shows that out of the US’s 164M power customers, 11% have dynamic pricing tariffs, of which 1% have real-time pricing, and the remainder are on fixed tariffs.
Where time-of-use tariffs have been successful, it hinges on a high pre-existing share of smart meters and strong customer awareness. Conversely, and somewhat demoralisingly, in an early roll-out of ToU tariffs in Spain, 78% of customers apparently did not even know they had ToU tariffs.
Strong potential for AI is suggested in the future, because many studies show real-time pricing is too complicated for people to track. People default to thinking about usage in larger time-blocks. But smart devices, with access to real-time power price data, may be well-suited to optimize loads.