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基于遗传优化支持向量机的变压器绕组热点温度预测模型

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Keywords: 油浸式变压器,绕组热点温度,支持向量机,遗传算法

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Abstract:

油浸式电力变压器的运行寿命及负载能力与绕组热点温度密切相关。精确预测变压器绕组的热点温度,是有效预防变压器热故障、准确预测变压器运行寿命和优化变压器设计的关键技术之一。论文研究了绕组热点温度支持向量机建模。为提高模型预测的精确度,选用径向基核函数优化模型结构;利用遗传算法对参数进行寻优。结合实验室模拟温升变压器绕组温度实测数据,提取输入和输出的特征量,并划分训练集和预测集,建立了基于遗传优化支持向量机的变压器绕组热点温度预测模型。实验表明应用本文模型预测结果与实测值基本一致,优于BP神经网络以及Elman神经网络的预测结果。

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