Persistence of excitation in an online monitoring of transformer: A system identification perspective

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作者

Shadab Nayyer Syed¹

1. Veermata Jijabai Technological Institute (VJTI), Mumbai, India

会议/活动

Power & Energy Society General Meeting (PESGM-22) 2022, July 2022 (虚拟会议)

海报摘要

For effective online monitoring to assess thermal performance and life expectancy, top-oil temperature (TOT) and hot spot temperature (HST) should be accurately estimated. The thermal-electrical analogy is used for the model based on the resistance-capacitance (RC) circuit to approximate the evolution of thermal performance. The Gradient-based estimation guarantees the convergence of the parameter estimation error to zero only when the persistence of excitation (PE) condition holds for regressor signals. As the choice of input-output data used for parameter identification is crucial, the design of experiment (DoE) is generally performed in the laboratory to satisfy PE conditions.

关键词

Hotspot, Top-oil temperature, Persistence of excitation, System identification, Tranformer

研究领域

Electrical Engineering

参考文献

1. D. Susa, M. Lehtonen, and H. Nordman, “Dynamic thermal modelling of power transformers,” IEEE Trans on Power Delivery, vol. 20, no. 1, pp. 197–204, Feb. 2005
2. B. C. Lesieutre, W. H. Hagman, and J. Kirtley, “An improved transformer top oil temperature model for use in an on-line monitoring and diagnostic system,” IEEE Trans on Power Delivery, vol. 12, no. 1, pp. 249–256.
3. Syed Shadab, J. Hozefa, K. Sonam, S. Wagh, and N. M. Singh, “Gaussian process surrogate model for an effective life assessment of transformer considering model and measurement uncertainties,” Int Journal of Electrical Power & Energy Systems, vol. 134, p. 107401, 2022.
4. Syed Shadab “Persistence of excitation in an Online Monitoring of Transformers", Power and Energy Society (PES) General Meeting (GM), 2022

基金

暂无数据

补充材料

暂无数据

附加信息

利益冲突

No competing interests were disclosed.

数据可用性声明

Data sharing not applicable to this poster as no datasets were generated or analyzed during the current study.

知识共享许可协议

Copyright © 2023 Syed. This is an open access work distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.