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Optimal Tuning for Load Frequency Control Using Ant Lion Algorithm in Multi-Area Interconnected Power System

机译:多区域互联电力系统中基于蚁群算法的负载频率控制优化调整

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This paper presents the use of a novel nature inspired meta-heuristic algorithm namely Ant Lion Optimizer (ALO), which is inspired from the ant lions hunting mechanism to enhance the frequency regulation and optimize the load frequency control (LFC) loop parameters. The frequency regulation issue was formulated as an optimal load frequency control problem (OLFC). The proposed ALO algorithm was applied to reach the best combination of the PID controller parameters in each control area to achieve both frequency and tie-line power flow exchange deviations minimization. The control strategy has been tested firstly with the standard two-area power system, followed by the IEEE three-area Western System Coordinating Council (WSCC) and, lastly, with the large three-area South-Western part of the Mediterranean interconnected power system (SWM): Tunisia, Algeria and Morocco. The dynamic performances of the test systems are compared to other approaches available in literature. The simulation results of this research show that ALO algorithm is able to solve LFC problem and achieve less frequency and tie-line power flow deviations than those determined by other methods used in this paper.
机译:本文介绍了一种新颖的自然启发式元启发式算法,即Ant Lion Optimizer(ALO),它是从蚂蚁搜寻机制中获得灵感的,以增强频率调节并优化负载频率控制(LFC)环路参数。频率调节问题被表述为最佳负载频率控制问题(OLFC)。所提出的ALO算法被应用于在每个控制区域中达到PID控制器参数的最佳组合,从而实现频率和联络线潮流交换偏差的最小化。首先使用标准的两区域电力系统对控制策略进行了测试,其次是IEEE三区域西部系统协调委员会(WSCC),最后是地中海互连网络的大型三区域西南区域(SWM):突尼斯,阿尔及利亚和摩洛哥。将测试系统的动态性能与文献中提供的其他方法进行了比较。仿真研究结果表明,ALO算法能够解决LFC问题,并且与本文使用的其他方法相比,能够实现更小的频率和联络线潮流偏差。

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