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首页> 外文期刊>International Journal of Electrical Power & Energy Systems >Robust estimation of power system harmonics using a hybrid firefly based recursive least square algorithm
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Robust estimation of power system harmonics using a hybrid firefly based recursive least square algorithm

机译:使用基于混合萤火虫的递归最小二乘算法对电力系统谐波进行稳健估计

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This paper presents a new and hybrid algorithm based on Firefly Algorithm (FA) and Recursive Least Square (RLS) for power system harmonic estimation. The hybrid FA-RLS algorithm is developed for estimating harmonics, inter harmonics and sub harmonics from a distorted and noise corrupted power signal. The basic strategy of the proposed algorithm is to integrate FA for getting the optimum initial weights for RLS algorithm that sequentially updates the unknown parameters (weights) of the harmonic signal. Simulation and practical validation is made with experimentation of the algorithms with real time data obtained from a solar connected inverter system. Comparison of results amongst recently proposed Artificial Bee Colony Least Square (ABC-LS), Bacteria Foraging Optimized Recursive Least Square (BFO-RLS) and FA-RLS algorithms reveals that proposed FA-RLS algorithm is the best in terms of accuracy, convergence and computational time. (c) 2016 Elsevier Ltd. All rights reserved.
机译:本文提出了一种基于萤火虫算法(FA)和递归最小二乘(RLS)的新型混合算法,用于电力系统谐波估计。混合FA-RLS算法被开发用于从失真和噪声破坏的功率信号中估计谐波,中间谐波和次谐波。所提出算法的基本策略是集成FA,以获取RLS算法的最佳初始权重,该算法依次更新谐波信号的未知参数(权重)。通过使用从太阳能逆变器系统获得的实时数据对算法进行实验,进行了仿真和实际验证。最近提出的人工蜂群最小二乘(ABC-LS),细菌觅食优化的递归最小二乘(BFO-RLS)和FA-RLS算法的结果比较表明,提出的FA-RLS算法在准确性,收敛性和稳定性方面是最好的计算时间。 (c)2016 Elsevier Ltd.保留所有权利。

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