Two-stage stochastic dual dynamic programming for transmission expansion planning with significant renewable generation and N-k criterion

Abstract

The large-scale integration of renewable energy sources (RES) is the global trend to deal with the energy crisis and greenhouse emissions. Due to the intermittent nature of RES together with the uncertainty of load demand, the problem of transmission expansion planning (TEP) is facing more and more challenges from uncertainties. In this paper, the TEP problem is modeled as a two-stage formulation, so as to minimize the total 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. Also, N-k security criterion is considered into the model, so the expansion plan can meet the required security criteria. The stochastic dual dynamic programming (SDDP) approach is applied to consider the uncertainties, and the whole model is solved by Benders' decomposition technique. Two case studies are carried out to compare the performance of the SDDP approach and the deterministic approach. Results show that the expansion plan obtained by the SDDP approach has a better performance than that of the deterministic approach.