A New Booster Inter-Area Virtual Transmission Lines for Robust Transmission and Generation Expansion Planning: A Data-Driven Approach with ESS Allocation, DER Flexibility, and Unit Commitment Ramping Constraints

This article presents a computational model for transmission and generation expansion planning that incorporates the effects of a new booster inter-area Virtual Transmission lines model, achieved through investments in energy storage systems within the transmission network areas. This approach enables the evaluation of potential reductions and deferrals in transmission line investments, including those involving inter-area trunk lines. Furthermore, the model captures flexibility from TSO-DSO interconnections to examine their influence on overall system expansion choices. A review of state-of-the-art flexibility indicators supports the selection of a metric that effectively quantifies resources for mitigating short-term operational variabilities; this metric is integrated into the model's unit commitment module, incorporating generator ramping and flexibility constraints. Flexibility is supplied to the AC transmission network via connected distribution systems at transmission nodes, with required flexibility levels derived from expansion planning performed by the associated DSOs. The model's core objective is to minimize total system costs, encompassing operations, investments in transmission and generation, and flexibility provisions. To handle uncertainties in demand and variable renewable energy generation, a data-driven distributionally robust optimization (DDDRO) method is employed. The framework utilizes a two-level architecture based on the column-and-constraint generation algorithm and duality-free decomposition, augmented by a third level to embed unit commitment and generator ramping constraints. Validation through case studies on the IEEE RTS-GMLC network illustrates the model's efficacy, highlighting the benefits of the proposed contributions in achieving cost savings, enhanced transmission and generation efficiency, and flexibility metrics.