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Adaptive Tolerant State Estimation under Model Uncertainty in Power Systems

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  • Ruizi Ma

    (College of Mechanical and Electrical Engineering, China Jiliang University, Hangzhou 310018, China)

Abstract

In this paper an adaptive tolerant estimator using singular value decomposition is proposed for a distribution network under model uncertainty in power systems. The adaptive tolerant estimator was designed with adjusted parameters and adjusted weights to overcome the limitations of model uncertainty. The estimator that reduces the measurement errors is adaptive to fast parameter changes in complicated environments. The singular value decomposition method was combined into the state estimator, which extended the over-determined cases to under-determined cases under model uncertainty. The performance of the tolerant estimator was compared with the conventional adaptive estimator, and the tolerant estimator showed accurate estimations against model uncertainty in complicated measurement environments.

Suggested Citation

  • Ruizi Ma, 2021. "Adaptive Tolerant State Estimation under Model Uncertainty in Power Systems," Energies, MDPI, vol. 14(8), pages 1-15, April.
    • Handle: RePEc:gam:jeners:v:14:y:2021:i:8:p:2111-:d:533463
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    References listed on IDEAS

    as
    1. Guo, Hengdao & Zheng, Ciyan & Iu, Herbert Ho-Ching & Fernando, Tyrone, 2017. "A critical review of cascading failure analysis and modeling of power system," Renewable and Sustainable Energy Reviews, Elsevier, vol. 80(C), pages 9-22.
    2. Benjamin Schäfer & Dirk Witthaut & Marc Timme & Vito Latora, 2018. "Dynamically induced cascading failures in power grids," Nature Communications, Nature, vol. 9(1), pages 1-13, December.
    3. Yang, Xuan & Zhang, Xiao-Ping & Zhou, Suyang, 2012. "Coordinated algorithms for distributed state estimation with synchronized phasor measurements," Applied Energy, Elsevier, vol. 96(C), pages 253-260.
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