Sample Complexity of Power System State Estimation using Matrix Completion

@article{Comden2019SampleCO,
  title={Sample Complexity of Power System State Estimation using Matrix Completion},
  author={Joshua Comden and Marcello Colombino and Andrey Bernstein and Zhenhua Liu},
  journal={2019 IEEE International Conference on Communications, Control, and Computing Technologies for Smart Grids (SmartGridComm)},
  year={2019},
  pages={1-7}
}
  • Joshua Comden, Marcello Colombino, +1 author Zhenhua Liu
  • Published 2019
  • Mathematics, Computer Science
  • 2019 IEEE International Conference on Communications, Control, and Computing Technologies for Smart Grids (SmartGridComm)
  • In this paper, we propose an analytical framework to quantify the amount of data samples needed to obtain accurate state estimation in a power system – a problem known as sample complexity analysis in computer science. Motivated by the increasing adoption of distributed energy resources into the distribution-level grids, it becomes imperative to estimate the state of distribution grids in order to ensure stable operation. Traditional power system state estimation techniques mainly focus on the… CONTINUE READING
    1
    Twitter Mention

    Figures and Topics from this paper.

    Explore key concepts

    Links to highly relevant papers for key concepts in this paper:

    References

    Publications referenced by this paper.
    SHOWING 1-10 OF 61 REFERENCES

    Matrix Completion for Low-Observability Voltage Estimation

    VIEW 6 EXCERPTS

    Distributed Robust Power System State Estimation

    VIEW 1 EXCERPT

    Recovering missing data via matrix completion in electricity distribution systems

    VIEW 1 EXCERPT

    A Low-Rank Matrix Approach for the Analysis of Large Amounts of Power System Synchrophasor Data

    VIEW 4 EXCERPTS
    HIGHLY INFLUENTIAL

    Power system state estimation: modeling error effects and impact on system operation

    VIEW 1 EXCERPT

    Robust Recovery of Missing Data in Electricity Distribution Systems

    VIEW 1 EXCERPT

    An integrated load allocation/state estimation approach for distribution networks

    VIEW 1 EXCERPT