Optimal integration of dynamic line rating and transmission expansion for sustainable grids: A mixed-integer linear programming approach with voltage stability constraints

Abstract

The rapid growth of electric demand and renewable integration has intensified transmission congestion, necessitating cost-effective grid expansion while ensuring operational security. This paper proposes a novel mixed-integer linear programming (MILP) model to co-optimize dynamic line rating (DLR) system placement and transmission network expansion planning (TNEP) under voltage stability constraints. The convex MILP formulation, solved to global optimality using GUROBI in GAMS, simultaneously minimizes costs while enforcing stability via loading margin constraints in wind-rich systems. Case studies on the IEEE 24-bus network demonstrate a 7 % cost reduction versus conventional TNEP, achieved by leveraging DLR’s dynamic capacity to reduce line upgrades. The model’s computational efficiency and scalability make it practical for real-world high-renewable and sustainable grid planning.