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Customer classification method using customer attribute information to generate the virtual load profile of non-automatic meter reading customer

机译:利用客户属性信息生成非自动抄表客户虚拟负荷曲线的客户分类方法

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To analyze the load of distribution line, real LPs (Load Profile) of AMR (Automatic Meter Reading) customers and VLPs (Virtual Load Profile) of non-AMR customers are required. Accuracy of VLP is an important factor to improve the analysis performance. There are 2 kinds of methods to generate the VLP; one is using ALP (Average Load Profile) per each industrial code and PNN (Probability neural networks) algorithm; the other is using LSI (Load Shape Index) and C5.0 algorithm. In this paper, existing researches are studied, and new method is suggested. Each methods are compared the performance with same LP data of real high voltage customers.
机译:为了分析配电线路的负载,需要AMR(自动抄表)客户的真实LP(负载曲线)和非AMR客户的VLP(虚拟负载曲线)。VLP的准确性是提高分析性能的重要因素。有 2 种方法可以生成 VLP;一种是使用每个工业代码的 ALP(平均负载曲线)和 PNN(概率神经网络)算法;另一种是使用LSI(荷载形状指数)和C5.0算法。本文对已有的研究进行了研究,并提出了新的方法。每种方法都与真实高压客户的相同LP数据进行了性能比较。

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