This article introduces a Wasserstein distance-based distributionally robust optimization model to address the transmission expansion planning considering wind turbine-powered microgrids (MGs) under the impact of uncertainties. The primary objective of the presented methodology is to devise a robust expansion strategy that accounts for both short-term variability and long-term uncertainty over the planning horizon from the perspective of a central planner. In this framework, the central planner fosters the construction of appropriate transmission lines and the deployment of optimal MG-based generating units among profit-driven private investors. Short-term uncertainties, stemming from variations in load demands and production levels of stochastic units, are modeled through operating conditions. The Wasserstein distance uncertainty set is used to characterize the long-term uncertainty about the future load demand. To ensure the tractability of the proposed planning model, the authors introduce a decomposition framework embedded with a modified application of Bender’s method. To validate the efficiency and highlight the potential benefits of the proposed expansion planning methodology, two case studies based on simplified IEEE 6-bus and IEEE 118-bus systems are included. These case studies assess the effectiveness of the presented approach, its ability to navigate uncertainties, and its capacity to effectively optimize expansion decisions.