This paper proposes an intelligent technique-based optimal controller for harmonics mitigation to maintain the power quality in renewable energy source (RES)-based distribution systems. The proposed intelligent technique is the joint execution of both the fractional-order proportional integral controller and moth-flame optimization with random decision forest. In the proposed approach, moth-flame optimization optimizes the dataset of fundamental and harmonic loop parameters such as terminal voltage and direct current voltage present in the hybrid shunt active power filter. The dataset is generated based on the linear and nonlinear load variation and parameter variation of the renewable energy sources, subject to the minimum error objective function. Based on the accomplished dataset, random decision forest accurately predicts the parameters and produces optimized control signals. The proposed technique guarantees the system with less complexity for the harmonics mitigation of the power quality event and hence the accuracy of the system is raised. Then, the proposed model is executed in the Matrix Laboratory/Simulink working platform and the execution is assessed with the existing techniques. The simulation analysis of the proposed approach is tested using the six test cases with various combinations of nonlinear loads. In all the test cases, the performance of various system parameters, such as source current with and without filter, source voltage, hybrid shunt active power filter current, load current and voltage, is analysed. Furthermore, the total harmonic distortion at different load ratings is also examined.

中文翻译：

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使用智能控制器连接可再生能源的混合并联有源电力滤波器中的谐波抑制

本文提出了一种基于智能技术的谐波抑制优化控制器，以维持基于可再生能源 (RES) 的配电系统的电能质量。所提出的智能技术是分数阶比例积分控制器和飞蛾火焰优化与随机决策森林的联合执行。在所提出的方法中，飞蛾火焰优化优化了混合并联有源电力滤波器中存在的基波和谐波环路参数的数据集，例如端电压和直流电压。该数据集是基于可再生能源的线性和非线性负载变化和参数变化生成的，受最小误差目标函数约束。基于完成的数据集，随机决策森林准确预测参数并产生优化的控制信号。所提出的技术保证了系统在降低电能质量事件的谐波方面具有较低的复杂性，从而提高了系统的准确性。然后，在 Matrix Laboratory/Simulink 工作平台中执行所提出的模型，并使用现有技术评估执行情况。使用具有各种非线性负载组合的六个测试案例来测试所提出方法的仿真分析。在所有的测试案例中，分析了各种系统参数的性能，如带滤波器和不带滤波器的源电流、源电压、混合并联有源电力滤波器电流、负载电流和电压。此外，还检查了不同额定负载下的总谐波失真。