A Novel Parameter Error Identification Method for Power Plant Dynamic Models

Date

2023-01-01

Author

Açılan, Etki
Göl, Murat

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Incorrect parameters in a power plant dynamic model affect the analysis results and control decisions in a power system, which may have serious consequences. The online calibration techniques in the literature utilize sensitivity analysis to determine the identifiable parameters before the calibration, and treat the majority of sensitive parameters as potentially erroneous. Hence, the candidate parameter subset for calibration mostly consists of “distractors,” i.e. highly sensitive but already correct parameters. The inclusion of distractors in the parameter calibration may decrease the accuracy of calibration, and increase the computation time. This paper proposes a method to identify erroneous parameters through the mismatch between collected PMU measurements and power plant model response. The proposed method relies on the classification of Recurrence Plots of the mismatch using 2-D Convolutional Neural Networks and identifies the erroneous parameters via the orthogonal decomposition. Hence, a smaller subset of candidate parameters is obtained by eliminating the distractors.

Subject Keywords

Biological system modeling, Calibration, Collinearity, convolutional neural networks, dynamic parameter estimation, identifiability, Phasor measurement units, Power generation, power plant parameter calibration, Power system dynamics, Sensitivity analysis, time series classification, Trajectory

URI

https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85149837282&origin=inward
https://hdl.handle.net/11511/102712

Journal

IEEE Transactions on Power Systems

DOI

https://doi.org/10.1109/tpwrs.2023.3253842

Collections

Department of Electrical and Electronics Engineering, Article

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Citation Formats

E. Açılan and M. Göl, “A Novel Parameter Error Identification Method for Power Plant Dynamic Models,” IEEE Transactions on Power Systems, pp. 0–0, 2023, Accessed: 00, 2023. [Online]. Available: https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85149837282&origin=inward.