电气工程学报 ›› 2021, Vol. 16 ›› Issue (4): 151-158.doi: 10.11985/2021.04.019

• 电力系统 • 上一篇    下一篇

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基于多维度分析的换流变预警技术研究与应用

周春阳1(), 李亚锦2(), 邓光武1(), 刘英男2(), 于大洋2()   

  1. 1.中国南方电网超高压输电公司广州局 广州 510000
    2.山东大学电气工程学院 济南 250061
  • 收稿日期:2021-05-27 修回日期:2021-07-15 出版日期:2021-12-25 发布日期:2022-02-10
  • 通讯作者: 李亚锦 E-mail:zcy8512@163.com;liyajin@sdu.edu.cn;guangwudeng@163.com;liuyingnan@sdu.edu.cn;yudayang@sdu.edu.cn
  • 作者简介:* 李亚锦,女,1989年生,硕士,助理研究员。主要从事电力系统优化建模与设计研究。E-mail: liyajin@sdu.edu.cn
    周春阳,男,1985年生,硕士,高级工程师。主要从事高压直流换流站设备运行及维护。E-mail: zcy8512@163.com
    邓光武,男,1977年生,硕士,高级工程师。主要从事高压直流输电技术研究及运行维护管理。E-mail: guangwudeng@163.com
    刘英男,男,1987年生,硕士,助理研究员。主要从事变电站在线监测及智能运维技术研究。E-mail: liuyingnan@sdu.edu.cn
    于大洋,男,1979年生,博士,副教授。主要从事电力系统优化技术研究。E-mail: yudayang@sdu.edu.cn

Multi-dimensional Analysis and Early Warning Model of Converter Transformer

ZHOU Chunyang1(), LI Yajin2(), DENG Guangwu1(), LIU Yingnan2(), YU Dayang2()   

  1. 1. Guangzhou Bureau EHV Power Transmission Company of CSG, Guangzhou 510000
    2. School of Electrical Engineering, Shandong University, Jinan 250061
  • Received:2021-05-27 Revised:2021-07-15 Online:2021-12-25 Published:2022-02-10
  • Contact: LI Yajin E-mail:zcy8512@163.com;liyajin@sdu.edu.cn;guangwudeng@163.com;liuyingnan@sdu.edu.cn;yudayang@sdu.edu.cn

摘要:

由于换流变设备运行环境和工况的差异性,相关运维规范设定的阈值在设备异常诊断方面具有一定的局限性。从工程实际应用出发,提出一种换流变多维度分析和预警方法,针对换流变重点监盘的关键参数建立温度、油位和冷却能力的多维度分析算法,对换流变当前状态进行评价。在多维度分析的基础上,提出基于长短期记忆网络的油温预测算法,实现换流变运行状态的趋势辨识。在±800 kV穗东站进行部署和应用算法模型,结果表明算法模型可有效识别出换流变运行状态异常。

关键词: 换流变, 在线监测, 多维度分析, 油温预测

Abstract:

Due to the difference of operation environment and working conditions of converter equipment, the threshold set by relevant operation and maintenance specifications has certain limitations in abnormal diagnosis. Based on the engineering application, a multi-dimensional analysis and early warning method is proposed. The multi-dimensional analysis algorithm of temperature, oil level and cooling capacity are established to evaluate the current state of converterfor the key parameters of converter transformer. On the basis of multi-dimensional analysis, the oil temperature prediction algorithm based on LSTM is proposed to realize the trend identification of the operation state of the converter. The algorithm model is deployed and applied in ±800 kV Suidong substation, and the results show that the algorithm model can effectively identify the abnormal operation state of converter transformer.

Key words: Converter transformer, online monitoring, multi-dimensional analysis, temperature prediction

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