569 / 2022-03-30 10:55:42
Remaining Life Estimation of Power Transformer Based on Wiener Process and Reliability Model
power transformer,life estimation,Wiener process,Reliability Analysis
终稿
Bo Li / Nanjing University of Aeronautics and Astronautics
Yuncai Lu / State Grid Jiangsu Electric Power Co. Ltd. Research Institute
Chao Wei / State Grid Jiangsu Electric Power Co. Ltd. Research Institute
Jun Jiang / Nanjing University of Aeronautics and Astronautics
Chaohai Zhang / Nanjing University of Aeronautics and Astronautics
Purpose/Aim

Remaining useful life (RUL) estimation of power transformer can effectively guarantee the stability of power grid operation and reduce the cost of equipment maintenance. A data-driven method, Wiener process is proposed for the insulation system, and Weibull distribution is adopted for other key components in this paper. Then, the system-level reliability model is established for the RUL calculation for oil-immersed power transformers.

Experimental/Modeling methods

For insulation system, dissolved gas in oil and degree of polymerization (DP) of insulation paper are employed for RUL estimation. The degradation state of insulation system is obtained by information fusion of historical data. Then, Wiener process is applied for RUL calculation. Finally, with Weibull distribution of other components like bushing, tap-changer, etc., the RUL distribution of the whole transformer is analyzed by series and parallel reliability model.

Results/discussion

The degradation data of insulation system is divided into two parts: training set and test set. The model is trained on training set, and then the trained model is applied for estimation the rest data. The comparison shows an error at about 30% between estimated data and test set.

Conclusions

This paper proposed a data-driven method for RUL estimation of insulation system, and a reliability model for power transformer considering key components. With these methods, the RUL of power transformer can be evaluated individually based on historical data, thus providing effective reference for maintenance strategy.

 
重要日期
  • 会议日期

    09月25日

    2022

    09月29日

    2022

  • 08月15日 2022

    提前注册日期

  • 09月10日 2022

    报告提交截止日期

  • 11月10日 2022

    注册截止日期

  • 11月30日 2022

    初稿截稿日期

  • 11月30日 2022

    终稿截稿日期

主办单位
IEEE DEIS
承办单位
Chongqing University
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