Dynamic Transmission Expansion Planning Using Adaptive Robust Optimization Under Uncertainties

The transmission expansion planning (TEP) problem is one of the perilous issues, which allows electricity transmission planners to design a cost-effective and reliable strategic model for the implementation of optimal transmission reinforcements in existing power grid networks. In this paper, a novel TEP model is proposed considering long- and short- term uncertain factors. The three-stage adaptive robust optimization (ARO) method deals with long-term uncertainties while prudently representing short-term uncertain parameters via scenarios. The formulated strategic scheme is elucidated through a modified decomposition algorithm that applies primal cutting planes and focuses on the subproblem feasible solution. The efficacy of the presented model is demonstrated through realistic case studies based on a 6-bus test system.