This paper introduces a new partitioned ant lion optimizer (PALO) strategy to improve the solution accuracy and quality of the optimal power flow (OPF) considering multi Static VAR Compensator (SVC) and Thyristor Controlled Series Controller (TCSC)-based FACTS devices. An interactive partitioning structure-based ALO is proposed to improve the solution of OPF by creating an interactive equilibrium between diversification and intensification during the search process. The decision variables such as active power, voltage magnitudes of generating units, tap transformers; reactive power of Static VAR Compensator (SVC), and the reactance of TCSC devices are optimized using a flexible partitioned process. Three objective functions, such as total fuel cost, total power loss, and total voltage deviation have been optimized considering load growth. The robustness of the proposed PALO has been validated on three test systems, the IEEE 30-bus, and two large test systems, the 300-bus and 2736 ps bus of the Polish power system. Results compared to many recent techniques prove the particularity and competitiveness of the proposed optimization strategy-based PALO.

中文翻译：

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考虑SVC和TCSC控制器的改进优化潮流解决方案使用新的分区蚁狮算法

本文介绍了一种新的分区蚁狮优化器 (PALO) 策略，以提高基于多静态无功补偿器 (SVC) 和晶闸管控制串联控制器 (TCSC) 的 FACTS 设备的最优潮流 (OPF) 的求解精度和质量。提出了一种基于交互式分区结构的 ALO，通过在搜索过程中创建多样化和集约化之间的交互式平衡来改进 OPF 的解决方案。有功功率、发电机组电压幅值、抽头变压器等决策变量；静态无功补偿器 (SVC) 的无功功率和 TCSC 设备的电抗使用灵活的分区过程进行优化。考虑到负载增长，优化了三个目标函数，例如总燃料成本、总功率损耗和总电压偏差。提议的 PALO 的稳健性已在三个测试系统、IEEE 30 总线和两个大型测试系统（波兰电力系统的 300 总线和 2736 ps 总线）上得到验证。结果与许多最近的技术相比证明了所提出的基于优化策略的 PALO 的特殊性和竞争力。