Coupled stochastic and robust transmission expansion planning

Abstract

To make the trade-off on the conservativeness of the robust optimization and the stochastic programming in transmission expansion planning (TEP) problems, a novel coupled stochastic and robust (CSR) optimization model for transmission expansion planning is proposed in this paper, which combines a scenario-based stochastic programming procedure with a bilevel robust optimization method. The stochastic programming procedure minimizes the total costs of the investment and the expected operation expenses under the worst-case scenario. Via the alternating iteration, an optimal transmission expansion schedule is obtained. Case study results demonstrate the cost-effective advantages of the proposed model over both stochastic TEP and robust TEP approaches. That is, the CSR solution greatly enhances the robustness of obtained schedule compared to the stochastic TEP approach, and meanwhile, it also prevents the unnecessary investment increment against the robust TEP approach.