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A modified artificial neural network (ANN) algorithm to control shunt active power filter (SAPF) for current harmonics reduction

机译:改进的人工神经网络(ANN)算法,用于控制并联有源电力滤波器(SAPF),以降低电流谐波

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摘要

Proliferation of nonlinear loads /devices in power systems generates a major concern to power system engineers, courtesy of its severe contamination effects (polluting the distribution networks with current harmonics). This paper depicts artificial intelligence (AI) application on resolving the power quality problem mentioned above by using the parallel active power filter (APF) strategy in two-wire distribution systems. The proposed AI adopted is an artificial neural network (ANN) responsible to detect current harmonics for the active power filtering process. The novelty control design is an artificial neural network (ANN) adopting a modified mathematical algorithm (a modified delta rule weight-updating W-H) and a suitable alpha value (learning rate value) which determines the filters optimal operation. The proposed scheme is achieved via simulation studies (under MATLAB SIMULINK environment) and results obtained are discussed to verify its performance.
机译:电力系统中非线性负载/设备的激增引起电力系统工程师的主要关注,这要归功于其严重的污染影响(用电流谐波污染配电网络)。本文描述了在两线配电系统中使用并行有源功率滤波器(APF)策略解决上述电能质量问题的人工智能(AI)应用。所采用的拟议AI是一种人工神经网络(ANN),负责为有源功率滤波过程检测电流谐波。新颖性控制设计是一种人工神经网络(ANN),它采用改进的数学算法(改进的增量规则权重W-H)和合适的alpha值(学习率值)来确定滤波器的最佳操作。通过仿真研究(在MATLAB SIMULINK环境下)实现了所提出的方案,并讨论了获得的结果以验证其性能。

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