We propose a new robust optimization approach to evaluate the impact of an intermittent renewable energy source on transmission expansion planning (TEP). The objective function of TEP is composed of the investment cost of the transmission line and the operating cost of conventional generators. A method to select suitable scenarios representing the intermittent renewable energy generation and loads is proposed to obtain robust expansion planning for all possible scenarios. A meta-heuristic algorithm called adaptive tabu search (ATS) is employed in the proposed TEP. ATS iterates between the main problem, which minimizes the investment and operating costs, and the subproblem, which minimizes the cost of power generation from conventional generators and curtailments of renewable energy generation and loads. The subproblem is solved by nonlinear programming (NLP) based on an interior point method. Moreover, the impact of an intermittent renewable energy source on TEP was evaluated by comparing expansion planning with and without consideration of a renewable energy source. The IEEE Reliability Test System 79 (RTS 79) was used for testing the proposed method and evaluating the impact of an intermittent renewable energy source on TEP. The results show that the proposed robust optimization approach provides a more robust solution than other methods and that the impact of an intermittent renewable energy source on TEP should be considered.