This paper proposes a distributionally robust optimization method for assessing economic benefits of transmission expansions with thyristor controlled series compensation devices. To accommodate the uncertainty of wind generations and electrical vehicle loads, a distributionally robust optimization method is proposed to use historical data instead of predefined distribution probabilities. In the proposed framework, firstly, a confidence set for unknown distributions are constructed based on the historical data. Then, based on worst-case distributions within a constructed confidence set, the optimal results of transmission expansion planning and allocation of thyristor controlled series compensation device are obtained. In order to take advantage of the flexible alternative current transmission devices (FACTS) in both economic and technical considerations, the optimal allocation of thyristor controlled series compensation is integrated into the transmission expansion planning. This requires AC-based transmission expansion planning model. AC power flow suffers from high computational complexity. To tackle this issue, the linearized AC power flow model is utilized. Furthermore, to solve the optimization problem, the combined technique including Bender's decomposition and cut-and-column are utilized. The numerical results on the Garver 6-bus and IEEE 118-bus systems demonstrate the effectiveness of the proposed method in comparison with scenario-based stochastic and robust optimization methods. Besides, the impacts of the thyristor controlled series compensation on total cost reduction has been investigated.