Optimizing Multi-Time Step Security-Constrained Optimal Power Flow for Large Power Grids

This work proposes a novel method for scaling multi-timestep security-constrained optimal power flow in large power grids. The challenge arises from dealing with millions of variables and constraints, including binary variables and non-convex, nonlinear characteristics. To navigate these complexities, techniques such as constraint relaxation, linearization, sequen-tial optimization, and problem reformulation are employed. By leveraging these methods, complex power grid problems are solved while achieving high-quality solutions and meeting time constraints. The innovative solution approach showcases great robustness and consistently outperforms benchmark standards.