DC Side Voltage Monitoring Model of Transformer based on Pattern Recognition

Aiming at the problem that the transformer DC side voltage is affected by the voltage quality during the monitoring process, its monitoring performance is greatly reduced. In order to improve the monitoring effect of the transformer DC side voltage, a transformer DC side voltage monitoring model bas...

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Bibliographic Details
Published in2020 IEEE International Conference on Industrial Application of Artificial Intelligence (IAAI) pp. 94 - 99
Main Authors Xian-Zhong, Liu, Wen-Mian, Shao
Format Conference Proceeding
LanguageEnglish
Published IEEE 25.12.2020
Subjects
AC voltage
average RMS mathematical relationship
DC side voltage
DC side voltage monitoring model
DC voltage transformer
discrete signal processing
Energy consumption
Mathematical model
mean square error methods
Monitoring
monitoring model
monitoring performance
OPP-CI model
pattern recognition
potential transformers
power supply quality
power system measurement
Process design
pure sinusoidal AC signal
RMS method
signal processing
transformer
voltage quality
Voltage transformers
ZIB node
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Summary:Aiming at the problem that the transformer DC side voltage is affected by the voltage quality during the monitoring process, its monitoring performance is greatly reduced. In order to improve the monitoring effect of the transformer DC side voltage, a transformer DC side voltage monitoring model based on pattern recognition is designed. Pattern recognition based on the RMS method using DC voltage transformer discrete signal processing using a pure sinusoidal AC signal with the average RMS mathematical relationship, by calculating the average of the AC voltage, indirectly, of the DC voltage transformer Valid values. From the OPP-CI model that ignores the influence of the ZIB node and the OPP-CI model that considers the influence of the ZIB node, pattern recognition is used to establish the transformer DC side voltage OPP-CI model, and the transformer DC side voltage monitoring process design is combined to realize the transformer DC Monitoring of side voltage. The experimental results show that the error of the monitoring results of the proposed model is relatively low, indicating that the method can improve the monitoring effect of the transformer DC side voltage.
DOI:10.1109/IAAI51705.2020.9332908