A Novel Framework for Co-Expansion Planning of Transmission Lines and Energy Storage Devices Considering Unit Commitment

This paper proposes a methodology for the co-expansion planning of transmission lines and energy storage devices, considering unit commitment constraints and uncertainties in load demand and wind generation. The problem is formulated as a mixed-integer nonlinear program (MINLP) and solved using a decomposition-based approach that combines a genetic algorithm with mixed-integer linear programming (MILP). Uncertainties are modeled through representative day scenarios obtained via clustering. The proposed methodology is validated on a modified IEEE 24-bus system. Results show that co-planning reduces wind curtailment, fuel costs, and total investment costs compared to transmission-only expansion.