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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蚂蚁狮子算法的负载频率控制最优调谐

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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性灵感的元启发式算法,即蚂蚁狮子优化器(ALO),这是从蚂蚁狮子狩猎机制的启发,以增强频率调节并优化负载频率控制(LFC)环路参数。频率调节问题被制定为最佳载荷频率控制问题(OLFC)。应用了所提出的alo算法以达到每个控制区域中PID控制器参数的最佳组合,以实现频率和扎线功率流量交换偏差最小化。控制策略首先用标准的两区域电力系统进行了测试,其次是IEEE三区西部系统协调委员会(WSCC),最后是地中海互联电力系统的大型三面积南部。 (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可用的其他方法进行比较。该研究的仿真结果表明,alo算法能够解决LFC问题并实现比通过本文所用的其他方法确定的频率和扎线功率流偏差。

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