Load flows are usually based on a Newton Raphson algorithm to solve a non-linear system of equalities. This approach has two limits:
-
More complex electrical devices behaviors are modeled with outer loops calling several Newton Raphson algorithms.
-
When the algorithm does not converge, it comes with no proof of infeasibility and with scarce information about the divergence origin.
By transforming the problem into an Optimal Power Flow (OPF), with the introduction of well-chosen slack and binary variables, it is possible to tackle those limits.
The intern will design and implement two new models for the existing OPF solver using Artelys Knitro, the leading non-linear optimization solver.
One model will tackle several devices behavior integrating them in the optimization problem with constraints and binary variables.
Second model will use slack variables and objective function to give more robustness and help to understand non-convergences.
Recent Comments