Frequency Adaptive Parameter Estimation of Unbalanced and Distorted Power Grid

Hafiz Ahmed, Mohamed Benbouzid, Mominul Ahsan, Alhussein Albarbar, Mohammad Shahjalal

    Research output: Contribution to journalArticlepeer-review

    22 Citations (Scopus)
    66 Downloads (Pure)


    Grid synchronization plays an important role in the grid integration of renewable energy sources. To achieve grid synchronization, accurate information of the grid voltage signal parameters are needed. Motivated by this important practical application, this paper proposes a state observer-based approach for the parameter estimation of unbalanced three-phase grid voltage signal. The proposed technique can extract the frequency of the distorted grid voltage signal and is able to quantify the grid unbalances. First, a dynamical model of the grid voltage signal is developed considering the disturbances. In the model, frequency of the grid is considered as a constant and/or slowly-varying but unknown quantity. Based on the developed dynamical model, a state observer is proposed. Then using Lyapunov function-based approach, a frequency adaptation law is proposed. The chosen frequency adaptation law guarantees the global convergence of the estimation error dynamics and as a consequence, ensures the global asymptotic convergence of the estimated parameters in the fundamental frequency case. Gain tuning of the proposed state observer is very simple and can be done using Matlab commands. Some guidelines are also provided in this regard. Matlab/Simulink based numerical simulation results and dSPACE 1104 board-based experimental results are provided. Test results demonstrate the superiority and effectiveness of the proposed approach over another state-of-the art technique.
    Original languageEnglish
    Article number8950095
    Pages (from-to)8512 - 8519
    Number of pages8
    JournalIEEE Access
    Publication statusPublished - 6 Jan 2020

    Bibliographical note

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    • Unbalance estimation
    • adaptive estimation
    • frequency estimation
    • phase estimation

    ASJC Scopus subject areas

    • Computer Science(all)
    • Materials Science(all)
    • Engineering(all)


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