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Optimal SSSC design for damping power systems oscillations via Gravitational Search Algorithm

机译:利用引力搜索算法优化电力系统振荡的SSSC设计

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In recent years, various heuristic optimization methods have been developed. Many of these methods are inspired by swarm behaviors in nature. In this paper, a new optimization algorithm namely Gravitational Search Algorithm (GSA) based on the law of gravity and mass interactions is illustrated for designing Static Synchronous Series Compensator (SSSC) for single and multimachine power systems. In the proposed algorithm, the searcher agents are a collection of masses which interact with each other based on the Newtonian gravity and the laws of motion. The proposed method has been compared with some well-known heuristic search methods. The obtained results confirm the high performance of the proposed method in tuning SSSC compared with Bacteria Foraging (BF) and Genetic Algorithm (GA). Moreover, the results are presented to demonstrate the effectiveness of the proposed controller to improve the power systems stability over a wide range of loading conditions. (C) 2016 Elsevier Ltd. All rights reserved.
机译:近年来,已经开发了各种启发式优化方法。这些方法中的许多方法都受自然界中群体行为的启发。针对单机和多机电力系统的静态同步串联补偿器(SSSC),设计了一种基于重力和质量相互作用定律的引力搜索算法(GSA)。在提出的算法中,搜索者主体是质量的集合,这些质量基于牛顿引力和运动定律彼此相互作用。将该方法与一些著名的启发式搜索方法进行了比较。与细菌觅食(BF)和遗传算法(GA)相比,所获得的结果证实了所提方法在调节SSSC方面的高性能。此外,结果表明了所提出的控制器在很大范围的负载条件下提高电力系统稳定性的有效性。 (C)2016 Elsevier Ltd.保留所有权利。

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