Derivative-Free Kalman Filtering Based Approaches to Dynamic State Estimation for Power Systems With Unknown Inputs

@article{Anagnostou2018DerivativeFreeKF,
  title={Derivative-Free Kalman Filtering Based Approaches to Dynamic State Estimation for Power Systems With Unknown Inputs},
  author={Georgios Anagnostou and Bikash C. Pal},
  journal={IEEE Transactions on Power Systems},
  year={2018},
  volume={33},
  pages={116-130}
}
This paper proposes a decentralized derivative-free dynamic state estimation method in the context of a power system with unknown inputs, to address cases when system linearization is cumbersome or impossible. The suggested algorithm tackles situations when several inputs, such as the excitation voltage, are characterized by uncertainty in terms of their status. The technique engages one generation unit only and its associated measurements, and it remains totally independent of other system… CONTINUE READING

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