提高电能质量的人工智能技术比较

S. Bangia, P. Sharma, Maneesha Garg
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引用次数: 8

摘要

人工智能技术是提高电能质量的最新趋势。本文分析比较了各种降低源电流谐波的人工技术。人工智能可以包括模糊逻辑和人工神经网络。仿真的目的是通过使用不能表示为“真”或“假”,而是“部分真”的概念,即模糊逻辑和神经元细胞的智能特征,来提高电能质量。并联有源滤波器是一种既能抑制源电流谐波又能补偿无功功率的控制器。迟滞电流控制器用于控制电压源逆变器的开关。采用D-Q框架理论产生基准补偿电流。利用电力系统工具箱在MATLAB环境下进行仿真。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Comparison of artificial intelligence techniques for the enhancement of power quality
Artificial Intelligence techniques are the recent trends used for the enhancement of power quality. This paper deals with analysis and comparison of different artificial techniques for harmonic reduction in the source current. Artificial Intelligence may include Fuzzy logic and Artificial Neural Network. The purpose of the simulation is to enhance the power quality by using the concepts that cannot be expressed as "true" or "false" but rather as "partially true" called as Fuzzy logic and intelligent features of the neuron cell. Shunt Active Filter is one of the controller that can be used for suppress the source current harmonics and compensates the reactive power. Hysteresis current controller is used to control the switching of Voltage Source Inverter. The D-Q Frame theory is used to generate the reference compensating current. Simulations are carried out in MATLAB environment using power system toolbox.
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