Please use this identifier to cite or link to this item: https://doi.org/10.1109/ACCESS.2020.2997728
Title: Online Estimation of Power System Inertia Constant under Normal Operating Conditions
Authors: Zeng, F.
Zhang, J.
Chen, G.
Wu, Z.
Huang, S.
Liang, Y.
Keywords: Ambient signals
Exponential smoothing
Inertia constant estimation
Sliding window
Step response
Subspace identification
Issue Date: 2020
Publisher: Institute of Electrical and Electronics Engineers Inc.
Citation: Zeng, F., Zhang, J., Chen, G., Wu, Z., Huang, S., Liang, Y. (2020). Online Estimation of Power System Inertia Constant under Normal Operating Conditions. IEEE Access 8 : 101426-101436. ScholarBank@NUS Repository. https://doi.org/10.1109/ACCESS.2020.2997728
Abstract: An online estimation method for the power system inertia constant under normal operating conditions is proposed. First of all, a dynamic model relating the active power to the bus frequency at the generation node is identified in the frequency domain using ambient data measured with the phasor measurement units (PMUs). Then, the inertia constant at the generation node is extracted from the unit step response of the identified model in the time domain using the swing equation. Finally, with the sliding window method and the exponential smoothing method, the estimated inertia constant is updated in real-time. Compared to the conventional methods using large disturbance data or field test data, the proposed method can estimate the inertia constant under normal operating conditions, and therefore, can provide the tracking trajectory of the power system inertia constant in real-time. The effectiveness of the proposed method is validated in the IEEE 39-bus system. The results show that the relative error of the identified inertia constant is below 5% and the identified inertia constant can be updated within 1s. © 2013 IEEE.
Source Title: IEEE Access
URI: https://scholarbank.nus.edu.sg/handle/10635/197830
ISSN: 21693536
DOI: 10.1109/ACCESS.2020.2997728
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