Simple ways to reduce your demand at peak time (and your bills too!):
- Aim to replace old appliances and fixtures with high energy efficiency models – LED light bulbs and other A++ appliances use up to 80% less electricity.
- Switch off appliances at the socket when not in use – for example XBox One S consumes about £17 a year in standby mode and about £7 per year of gaming 9 hours a week (assuming 15 p/kWh).
- Be efficient at cooking – put lids on pots, combine boiling and steaming and use slow-cooker during the day.
- Try to use one high-power appliance at a time – choose one: electric cooker and oven or electric shower.
- Avoid running dishwasher, washing machine or tumble drier between 4 and 8 pm – lookout for the sun or use delay function to postpone the start into the night.
Is it worth switching to Time-of-Use tariff? There is no easy answer here because it depends on the design tariff, what you do and what appliances are on during the peak-time of the tariff – We are working on this one.
Any transition brings about change which could potentially disrupt the more vulnerable and strengthen those who have capital means. The transition to Time of Use tariffs will present similar challenges with opportunities for progress which benefits many and accounts for the impact of transitions on vulnerable consumers.
Our projects’ findings will provide recommendations on who will potentially be worse off from Time of Use tariffs. This will enable consumer groups’ awareness of the societal benefits and costs of transitioning to Time of Use tariffs.
Suppliers could benefit from the project findings by:
- Knowing how the proposed Time-of-Use tariffs could impact their customers.
- Recruit more consumers by demonstrating the benefits of Time-of-Use tariffs.
- Benefiting from alternative segmentation of their consumers’ base.
- Clustering of consumers based on periods of active occupancy will improve the accuracy of different types of tariffs.
Project findings are expected to support policy makers by:
- Ensuring consumer protection through transitions to Time of Use tariffs
- Quantification of contribution to peak residential electricity demand of different categories of users
Project findings could support decision making in :
- Deploying smart technologies to support areas with consumers who are unable to take advantage of their flexibility
- Identifying type of engagement with consumers to maximise the effect
- Demand profiles of network modelling and planning based on socio-demogrpahic information of the residents