Under increasing adoptions of climate neutrality paradigms, this dissertation demonstrates that analytical frameworks need to capture cross-sectoral interactions when analysing large-scale planning problems for low-carbon energy and power systems. A mathematical programming framework is presented that features a sector-integrated approach toward modelling and optimising transmission investment decisions in low-carbon energy scenarios. By exploiting the optimisation problem structure with tailored decomposition stages, a novel solution strategy optimises the otherwise intractable large-scale problem instances efficiently. The proposed bundle method implementation solves the mixed-integer problems on a distributed computational platform and recovers high-quality primal solutions. Finally, this dissertation addresses two main research objectives with a large-scale cross-sectoral capacity expansion and long-term cross-border transmission expansion study for the future integrated European system that shows the impact of transport sector flexibility on offshore grid investment decisions in the North Seas and the welfare distributional effects in direct and indirect neighbour countries.weiterlesen