Thermal Monitoring of Transformer via Finite Time Parameter Estimator

S. Yaqub, B. Devangee,G. Revati,Syed Shadab, S. R. Wagh

2023 9th International Conference on Control, Decision and Information Technologies (CoDIT)(2023)

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摘要
In transmission and distribution substations, power transformers account for the majority of capital investment. As they are expensive, effective thermal performance monitoring is necessary for life extension. The hot-spot temperature value is among the most significant factors affecting a transformer's life expectancy. As HST evaluation require some Top-oil Temperature model parameters, accurate estimations of TOT are required to analyze the thermal performance and lifespan of transformers. Conventionally, the TOT parameters from the Resistance-Capacitance network are determined using the input-output data. While the regressor signals meet the Persistence of Excitation criterion in the Gradient Estimator a parametric estimate error approaches zero and the parameter converges to their true value. The Design of Experiment is often carried out in the test center to meet the PE requirement. As a consequence, actual operating transformer data is utilized for the identification and estimation of the parameters associated with the TOT model by using finite-time estimators. The detected PE issue, the impact of DoE, and the efficiency of FTEs with different filters for non-PE data obtained from the actual operating transformers' thermal model are demonstrated by experimental analysis using MATLAB.
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关键词
Finite-time estimators (FTE),Gradient estimators (GE),HST,Memory Regressor Extension,Top-oil Temperature (TOT)
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