Identifiability Analysis for Power Plant Parameter Calibration in the Presence of Collinear Parameters

Date

2021-01-01

Author

Açılan, Etki
Göl, Murat

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IEEEA good quality stability model is a key factor for accurate power system operations. Inaccurate parameters of the stability models affect the decision making which paves the way for serious consequences. Thus, it is necessary to calibrate the stability model parameters in a regular manner. There are several calibration methods in the literature which are based on simultaneous estimation of the parameters and states. However, not all of the model parameters are well estimable simultaneously. Simultaneous estimation of parameters with high collinearity may result in biased calibration results. In this paper, the trajectory sensitivity method is used to detect the sensitive parameters and construct the sensitivity matrix. Then, parameters with high linear dependency are identified using the sensitivity matrix. It is shown that, despite the high sensitivity of a parameter, its estimability degrades as the collinearity with other parameters increase. In this paper an identifiability analysis that detects the collinearity among the sensitive parameters is proposed. The proposed method is validated using WSCC 9-Bus System.

Subject Keywords

Analytical models, Calibration, Collinearity, Dynamic Parameter Estimation, Estimation, Identifiability, Mathematical models, Power generation, Power Plant Model Validation, Power Plant Parameter Calibration, Sensitivity Analysis, Sensitivity analysis, Voltage measurement

URI

https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85120046176&origin=inward
https://hdl.handle.net/11511/94980

Journal

IEEE Transactions on Power Systems

DOI

https://doi.org/10.1109/tpwrs.2021.3130076

Collections

Department of Electrical and Electronics Engineering, Article

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Citation Formats

E. Açılan and M. Göl, “Identifiability Analysis for Power Plant Parameter Calibration in the Presence of Collinear Parameters,” IEEE Transactions on Power Systems, pp. 0–0, 2021, Accessed: 00, 2021. [Online]. Available: https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85120046176&origin=inward.