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Complementary Module to Smart Meters Based on Outliers Correction Using Artificial Intelligence

机译:基于异常值校正的互补模块使用人工智能校正

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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. In this way, the distribution scenario analysis is damaged by false and/or absence data. This work proposes a new module to complement the Smart Meters. Two algorithms for outlier correction were developed using artificial intelligence techniques: fuzzy logic and neural networks. To demonstrate the developed methods applicability, a case of study is performed with real substation data. The results were relevant and demonstrated the two proposed algorithms feasibility.
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。以这种方式,分布方案分析因虚假和/或缺位数据损坏。这项工作提出了一个新的模块来补充智能电表。使用人工智能技术开发了两种转型校正算法:模糊逻辑和神经网络。为了证明所开发的方法适用性,使用实际变电站数据进行研究。结果是相关的,并证明了这两个提出的算法可行性。

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