  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 nonconvex, nonlinear characteristics. To navigate these
complexities, techniques such as constraint relaxation, linearization,
sequential 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.
