基于GP-NLSM的变压器绕组热点温度建模
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国家电网有限公司科技项目(5400-202056131A-0-0-00)


Hot spot temperature prediction model of transformer based on GP-NLMS
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    摘要:

    准确的绕组热点温度估算模型是评估油浸式变压器热状态和绝缘寿命的关键。文中基于变电站监测的热点温度与负载电流数据,利用遗传编程算法训练出热点温度估算模型的基本结构,结合归一化自适应滤波(NLMS)算法实现热点温度估算模型的参数辨识,最终建立一种油浸式变压器热点温度显式预测模型。研究结果表明:显式绕组热点温度估算模型可以直观映射出负载系数与绕组热点温度之间的关系。预测集下模型的拟合优度为0.998 8,最大绝对误差仅为1.36 ℃,验证了模型的正确性与有效性。此外,针对同一区域下同种容量型号的油浸式变压器进行绕组热点温度估算,证明了所提模型具有较强的泛化性能。

    Abstract:

    An accurate estimation model of winding hot spot temperature is the key to assess the thermal state and insulation life of oil-immersed transformers. Based on the hot spot temperature and load current monitored by the substation,the genetic programming algorithm is applied to train the basic structure of the hot spot temperature estimation model. Then,the parameter identification of the hot spot temperature estimation model is performed by the normalized least square mean (NLMS) algorithm. Finally,an explicit prediction model of the hot spot temperature is established for oil-immersed transformers. The explicit winding hot spot temperature estimation model can effectively reflect the relationship between the load factor and the winding hot spot temperature. Moreover,the goodness of fit of the model under the test set is 0.998 8,and the maximum absolute error is only 1.36 ℃,which verify the correctness and effectiveness of the model. Furthermore,the strong generalization performance of the proposed model is proved by estimating the winding hot spot temperature for oil-immersed transformers with the same capacity and model in the same area.

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张军,陈霄,张旺,诸德律,陈英华.基于GP-NLSM的变压器绕组热点温度建模[J].电力工程技术,2022,41(5):165-171

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  • 收稿日期:2022-03-25
  • 最后修改日期:2022-06-18
  • 录用日期:2021-06-28
  • 在线发布日期: 2022-09-21
  • 出版日期: 2022-09-28