Two-stage stochastic dual dynamic programming for transmission expansion planning with significant renewable generation

As the increasing integration of renewable energy sources (RES), the problem of transmission expansion planning (TEP) is facing more and more challenge from the uncertainties of loads and RES generations. In this paper, a two-stage mathematical model for the TEP problem is presented to minimize the sum of investment costs and generation costs. To ensure the utilization level of the RES generation, the expansion plan is required to provide sufficient transmission capacity for the integration of RES. The stochastic dual dynamic programming (SDDP) approach is applied to consider the uncertainties, and the whole model was solved by the Benders decomposition technique. Two case studies were carried out to compare the performance of the SDDP approach and the deterministic approach.