This PhD project focuses on uncertainty quantification in grid calculations.
Worst-case scenario
Currently, the calculation rules used for the energy grid are quite outdated, especially considering the rapid changes in energy usage. When the grid operator evaluates whether a new customer can be connected to the grid, they make predictions about the expected energy usage and return. These predictions always consider worst-case scenarios to ensure grid reliability. However, relying on an accumulation of worst-case scenarios and average estimations can lead to overly pessimistic assessments of the grid's capacity. This results in limiting the number of new connections to the grid, which is a pressing issue across the country.
Towards optimal use
By estimating the likelihood of worst-case scenarios and considering the probability of multiple worst-case scenarios occurring simultaneously, we can gain insights into more optimal grid usage. This approach could enable Alliander to add more connections to the grid without requiring significant material changes to the infrastructure.
