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.

中文翻译：

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受安全约束的 ACOPF：结合最坏的突发事件和离散控制器

本文报告的工作旨在为系统运营商开发一种算法，以解决稳健的安全约束交流最优潮流 (R-SC-ACOPF) 问题，该算法还优化了离散控制器的设置，包括负载抽头变换器 (LTC) 和并联电容器组 (SCB)。提出了一种涉及主问题和多个子问题的迭代算法。主问题通过考虑基于子问题识别的单组件最坏意外事件的原始 SC-ACOPF 约束来选择最佳离散控制器设置。每个子问题都是一个双层最大最小问题，用于寻找当前最坏的意外事件。总体目标是最小化总成本，包括发电和减载成本，同时满足所有相关约束。主问题和子问题允许使用二进制变量表示 LTC 抽头位置、SCB 状态和突发事件。介绍了两个案例研究作为这种新技术的应用。