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基于电表冻结数据的台区户-相识别技术研究

Overview of Status Evaluation Techniques for Distribution Transformers

  • 摘要: 研究了一种基于改进遗传算法的户-相识别技术。该方法首先通过数据处理对配电台区的数据进行挖掘,为算法的实现提供数据基础;其次,在遗传算法的基础上增加检测判断环节对算法进行改进,提高算法速度;最后,确立正确的目标函数,以实际台区结构为基础进行建模测试,结果表明基于改进遗传算法的户-相识别技术可以有效判别户-相关系,可为配电台区拓扑的自动化识别提供便捷条件。

     

    Abstract: A household phase recognition technology based on improved genetic algorithm was studied. This method first mines the data of the distribution station area through data processing for algorithm implementation. Secondly, adding detection and judgment steps on the basis of genetic algorithm to improve the algorithm and increase its speed. Finally, establish the correct objective function and conduct modeling tests based on the actual substation structure. The results show that the improved genetic algorithm based household phase recognition technology can effectively distinguish household correlation systems and provide convenient conditions for meter reading systems.

     

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