Skip to main content

Your web browser is out of date. Please update it for greater security, speed and the best experience on this site.

Choose a different browser

Analysing the impact of Time-of-Use tariffs

Close up shot of the controls of a washing machine.

Modelling the effect on customers’ bills based on their usage.

Project duration: September 2013 to April 2014

The rollout of smart meters is enabling electricity suppliers to deploy new Time-of-Use (ToU) based approaches to pricing electricity. The tariffs encourage customers to shift demand from peak to off-peak periods or to simply reduce peak demand. Both cases reduce system costs and improve system efficiency.

However, there are variations in the ability of different customers to take advantage of ToU tariffs, depending on their current pattern of electricity usage and their willingness or ability to respond. Understanding the scale and nature of these variations is important to the design of effective ToU tariffs and to consider how consumer interests may be protected as such tariffs become available.

To support its early consideration of the potential impacts of ToU tariffs on domestic electricity consumers in the UK, energy regulator Ofgem commissioned CSE to undertake analysis and modelling of domestic electricity use patterns.

Close up shot of the controls of a washing machine.
What time do people put the washing machine on? Would a Time-of-Use tariff help them with their bills?

Developing analytical and modelling techniques

Both the limited availability of data which combines domestic ToU electricity consumption patterns with consumer socio-demographic characteristics, and the limited evidence of how different consumers might respond to ToU tariffs (by changing their demand patterns), inevitably constrained the scope of this analysis. It focused primarily on developing analytical and modelling techniques. These techniques could subsequently be applied to more comprehensive data and evidence as it became available. CSE used the half-hourly smart electricity demand dataset collected during the Energy Demand Research Project (EDRP) [1].

To support the analysis, CSE:

  1. Used cluster analysis to identify a set of archetypal weekly demand profiles.
  2. Created a half-hourly tariff model to calculate the electricity bills of approximately 5,000 EDRP cases based on three example ToU tariffs defined by Ofgem which were then compared with a representative standard non-ToU tariff.

Paving the way for future research

This initial exploratory research did not model consumer response to ToU tariffs and was limited to three static ToU tariffs. In reality, many different types of ToU tariff are likely to develop in the future and each type is likely to have different impacts on consumers. The findings from this research demonstrate the importance of (a) developing our capability to understand these impacts in more detail and (b) ensuring that consumers are well informed about both their energy use and the types of ToU tariffs on offer before switching to these more innovative types of tariff.

The work demonstrates the value of collecting and analysing half-hourly smart electricity meter data. Future research could extend the techniques used here to much larger data samples, offering opportunities to support regulatory and policy development work in the domestic electricity arena.


[1] The EDRP was a two-year trial of domestic smart meters and energy demand reduction interventions which ran from 2008-2010. It was part-funded by DECC, managed by Ofgem, and run by four energy suppliers.


Share this: