Abstract

The work reported in this paper aims at developing an algorithm for system operators to solve a robust security-constrained AC optimal power flow (R-SC-ACOPF) problem, which also optimizes the settings of discrete controllers including load tap changers (LTCs) and shunt capacitor banks (SCBs). An iterative algorithm involving a master problem and a number of sub-problems is proposed. The master problem selects the optimal discrete controllers' settings by taking into account primal SC-ACOPF constraints based on the single-component worst contingencies identified by the sub-problems. Each sub-problem is a bi-level max-min problem used to find the current worst contingency. The overall objective is to minimize the total cost, including generation and load shedding cost, while satisfying all relevant constraints. The master problem and sub-problems allow representing LTC tap positions, SCB status, and contingencies using binary variables. Two case studies are presented as applications of this novel technique.

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