Clustered Profiles

What are Clustered Profiles ?

In the optimization process, AI-generated clustered profiles are used to enhance performance. These profiles are created by grouping similar daily patterns from all hourly input data in Sympheny, including Energy Demand, On-site Resources, and Hourly Tariffs. While a reduced number of representative days (referred to as Typical Days) is selected, the model still operates in hourly time steps, ensuring that variations within each day are preserved. The clustered profiles enable the reconstruction of the full annual profile using these representative days.

Note that these profiles remain consistent across all solutions within a given scenario. Additionally, the clustering is performed for each Stage, meaning that all profiles used in a stage are clustered together.

How are Typical Days Generated ?

The Sympheny engine selects a specific number of typical days based on the overall hourly profiles provided and the chosen Temporal Resolution. These typical days are selected from the 365 possible days in a year, based on patterns identified across the combined profiles.

The Clustered Profiles are created from selected typical days, which are repeated throughout the year. For instance, if 20 typical days are chosen, each of these days, comprising 24 hours, will be used to represent the entire year, filling in the 365 days.

Each typical day is linked to specific data across all profiles, ensuring that the original days are not mixed and matched. This means that a typical day will consistently represent the same day across all profiles, rather than using different days for different profiles. Each typical day consists of 24 hours multiplied by the number of profiles.

For example, in a system with two demand profiles (Heating and Electricity), if a typical day represents days 5, 8, 12, 23, 36, and 45 for the Heating profile, it will also represent those same days for the Electricity profile.

Temporal Resolution

The number of typical days selected is determined by the Temporal Resolution chosen during the execution step.

The termination criteria specify the number of typical days allowed within a defined range, set by the minimum and maximum limits:

• Low:

  • Minimum days: 5

  • Maximum days: 50

  • Termination criteria:

    • Max load duration error: 15%

    • Max sum error: 2%

• Medium:

  • Minimum days: 15

  • Maximum days: 100

  • Termination criteria:

    • Max load duration error: 7.5%

    • Max sum error: 1%

• High:

  • Minimum days: 30

  • Maximum days: 200

  • Termination criteria:

    • Max load duration error: 3%

    • Max sum error: 0.5%

Additionally, the clustering process ensures that the non-zero maximum and minimum values of each profile are preserved. It also maintains the linear combination of the profiles, meaning that the peaks of two or more profiles occurring at the same time step are conserved.

Clustered Profiles Metrics

The Clustered Profiles will exhibit a similar load duration curve as the original profiles, while ensuring that both the sum and peaks of the profiles are preserved. In the results folder, the file Output.xlsx, which can be downloaded once the optimization is complete, contains a sheet titled Clustered Profiles-[Scenario Name].xlsx that provides the following metrics:

• Number of Typical Time Steps:
  This represents the total number of time steps calculated as 24 x Typical Days.

• Max Load Duration Error (%):
  The maximum load duration error across all profiles.

• Max Sum Error (%):
  The maximum sum error across all profiles.

The error function used to calculate these metrics is the Symmetric Mean Absolute Percentage Error (SMAPE) for each profile, from which the maximum error percentage is derived.