Challenge and objective

  • How to calculate customer baseline load (CBL), using different methodologies and having finer time resolution data (5 minutes) from a real-life office building.
  • Analyze the accuracy depending on measurement point in the system.
  • Analyze the accuracy of different methods.

Work performed

  • Analyzed input data at office-building level and at EV parking-lot level, compared their accuracy.
  • Implemented existing CBL-calculation methods, both before/after measurements, and historical data points.

Significant results

  • Using flexibility for internal goals using the EV-chargers influence the accuracy of using historical data when measuring on the EV parking-lot level.
  • Using measurements before/after activation is very accurate during midday at the building-level, due to a 200-kW limit on import.
  • Seasonal variation in historical data influence the accuracy, especially with seasonal internal goals such as the 200-kW limit only during winter.

Impact for distribution system innovation

  • The methods can be applied to predict the baseline load from a flexible user during flexibility activation.
  • Important to be aware of internal flexible measures that could affect historical data accuracy.


Figure left: CBL using before/after measurement
Figure right: Using historical data to predict the CBL

Magnus Korpås

WP3 Lead
+47 970 42 009
Magnus Korpås
WP3 Lead


Reference in CINELDI

  • K.E. Thorvaldsen: "Calculation of Customer Baseline Load with different methodological approaches", CINELDI-memo, 2022.