Challenge and objective

  • Load modelling is an important part of distribution grid planning to account for uncertainties and risks associated with load demand. A code platform is needed to analyse smart meter data and test the implications of different load modelling approaches.

Work performed

  • A code base was developed through a summer internship at SINTEF Energy Research, and continued work in 2021/2022.
  • One example of a stochastic load modelling method (PhD work by Erling Tønne) is implemented.
  • Load and grid data for the Øra Industrial area is used for testing in collaboration with Norgesnett in the pilot "Probabilistic planning methodology".

Significant results

  • A modular and flexible code platform implemented in Python for pre-processing and managing historic load demand data in a grid area, apply load modelling method(s), analysing the need for flexibility and run "what-if" analyses.

Impact for distribution system innovation

  • Testbed for incorporating new load modelling approaches in distribution grid planning.
  • Starting point for analysing, e.g., i) risks due to load uncertainty and ii) needs for flexibility in a grid area.
Code platform flexible load analysis

Susanne Sandell

WP1 Lead
+47 984 891 26
Susanne Sandell
WP1 Lead

Reference in CINELDI