Generation and transmission expansion planning (GTEP) faces increasing challenges from variable renewable energy integration, inter-area transmission congestion, and the need for cost-effective flexibility. This study extends a prior data-driven distributionally robust optimization framework by introducing inter-area virtual transmission lines (VTL), enabled through strategic energy storage system (ESS) allocation within network areas, to optimize and potentially defer investments in trunk transmission lines, while adding a unit commitment (UC) level considering ramping constraints to address short-term net demand variability. The model incorporates flexibility from transmission and distribution system operators interconnection (TSO-DSO), quantified via a selected state-of-the-art metric integrated into ramping and flexibility constraints, with required levels derived from associated DSO planning. A linear AC optimal power flow is employed, and uncertainties in demand and variable renewable generation are handled using data-driven distributionally robust optimization within a three-level architecture: column-and-constraint generation with duality-free decomposition at the core, augmented by unit commitment. Case studies on the IEEE RTS-GMLC network demonstrate significant reductions in total system costs (operations, investments, and flexibility provisions), improved transmission efficiency, and enhanced flexibility metrics, confirming the value of localized ESS deployment and high-resolution ramping in modern low-carbon power systems.
Ferreira et al. (Fri,) studied this question.