With an increasing integration of fluctuating renewable generation into power grids, the challenge to ensuring the security of supply with controllable generators increases. In this context, the necessity to consider grid restrictions for the generator placement decision is gaining in importance. For an adequate decision support, models are needed which are able to provide an N-1 secure optimal placement of generators under dierent grid load situations. In large-scale power system models the solution of such a problem requires new approaches as timecoupling constraints imposed by power storages increase the size of an already hard to solve N-1 secure optimal power flow (OPF) problem with binary special ordered set type restrictions for the generator placement. Based on a hierarchical augmented Lagrangian approach we are able to decompose the time coupling restrictions and solve the generator placement problem for smaller subsets of coupled hours. We demonstrate our approach for the German transmission in 2030 based on a DC-approach for the dynamic OPF. The increasing importance of an integrated European electrical network for the se ... mehrcurity of supply is addressed by embedding the problem within a European transport problem. Our results indicate a high sensitivity of the optimal generator placement depending on the grid load scenario, while the lack of dominating solutions for the entire time horizon emphasis the need for an advanced time-coupled optimisation technique.