Robust AC Transmission Expansion Planning with Load and Renewable Generation Uncertainties

Abstract

With the integration of Renewable Energy Sources (RESs), the power network must be robust to handle the system's uncertain scenarios. DC Transmission Expansion Planning (TEP) plans are generally not feasible for the AC network. A first bilevel Robust Optimization (RO) solution approach for AC TEP with injection uncertainties in loads and RESs generations is proposed in this paper. It utilizes a well-known convex relaxation and is solved by Benders Decomposition (BD), where the master determines the robust AC TEP plan. A novel dual slave model is developed for the second level of BD, which circumvents the issues in using the Conic Duality Theory (CDT), and aids in the worstcase realization of uncertainties using a novel set of constraints. The developed dual slave is not a mixed-integer problem and is solved using the Primal-Dual Interior Point Method (PDIPM). The proposed work also uses additional linear constraints to reduce BD's computational burden and direct the master towards optimality. Monte-Carlo Simulation (MCS) based verification, via actual nonlinear and non-convex AC Optimal Power Flow (OPF), proves 100% robustness of the TEP plans for all scenarios.