Scalable Solutions for Security-Constrained Optimal Power Flow With Multiple Time Steps

This work introduces an innovative approach to scaling security-constrained optimal power flow problems to large power grids with multi-timestep, addressing the significant challenges associated with managing millions of continuous and integer optimization variables as well as nonlinear and nonconvex constraints. Through a strategic combination of problem reformulation, linearization methods, constraint-relaxation techniques, and sequential optimization, the complexities inherent to large power grid optimization are effectively navigated. The proposed methodology enables the resolution of complex power grid models with strict time constraints while attaining high-quality solutions. Demonstrating remarkable robustness, the novel approach consistently surpasses established benchmark methods.