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Algoritmos de Corre??o de Outliers para Curvas de Potência utilizando inteligência artificial

机译:异常值使用人工智能的功率曲线正确算法

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One of the main problems of the data acquired by power utilities is the presence of outliers affecting the database measurements in the electrical system, damaging the analyzes of the distribution scenario. This work proposes a new module to complement the measurements made by the utilities. Two algorithms for outliers correction were developed using artificial intelligence techniques: fuzzy logic and artificial neural networks. The first technique, with a fuzzy approach, develops an inference system based on the variations of previous measurements to determine future variation. In the second algorithm developed using NN, the outliers were filled using a prediction model using 10 previous samples. To demonstrate the applicability of the developed methods, a case study is performed on a substation in a city of Paraíba.
机译:电力实用程序获取的数据的主要问题之一是存在影响电气系统中数据库测量的异常值,损坏分配方案的分析。这项工作提出了一个新的模块,以补充公用事业公司所做的测量。使用人工智能技术开发了两种异常校正算法:模糊逻辑和人工神经网络。具有模糊方法的第一技术,基于先前测量的变体来开发推理系统以确定未来的变化。在使用NN开发的第二算法中,使用10个以前的样本使用预测模型填充异常值。为了证明所开发方法的适用性,在帕拉博市的变电站上进行案例研究。

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