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.
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".
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.