My house has seasonal energy profiles

Some households experience significant variations in their electricity usage throughout the year. This article explains how Automised Energy accounts for these seasonal differences when finding your best-fit electricity plan.

How seasonal usage affects plan matching

Seasonal variations in energy usage are common and can be caused by:

• Heating and cooling needs changing with the weather
• Daylight hours affecting lighting requirements
• Solar generation differences between summer and winter
• Holiday periods altering household occupancy

These changes can impact which electricity plan offers the best value across an entire year.

How we account for seasonal variations

Automised Energy's plan matching system addresses seasonal usage patterns in several ways:

1. 12-month data collection: Where possible, we analyse a full year of your electricity usage history, capturing your consumption across all seasons.
2. Seasonal tariff assessment: Our calculations evaluate plans with seasonal tariff structures against your usage patterns, identifying if these align well with your specific seasonal variations.
3. Annual cost projection: Rather than focusing on a single month or season, we calculate total costs across a full annual cycle to identify the best overall plan.

Seasonal plans vs year-round plans

Some electricity retailers offer plans with different rates for different seasons. Our system evaluates these alongside standard year-round plans to determine which provides the best overall value based on your specific usage patterns.

If a plan with seasonal tariff structures matches your seasonal usage patterns well, it will likely be identified as a good fit in our analysis.

Future enhancements

We're continually improving our system and value your input on additional features. If you'd like more control over how seasonal data is used in calculations, please let us know.

Potential future options might include:

• Selecting specific date ranges for inclusion in calculations
• Prioritising certain seasonal periods in the analysis
• Customising seasonal weightings based on expected changes

To provide feedback on these potential features or suggest others, please contact our support team.