Distribution network state estimation method based on improved generalized maximum likelihood estimation Academic Article uri icon

abstract

  • Aiming at the similarities and differences in the data composition, data accuracy and refresh frequency of different measurement data in distribution network state estimation, a new estimation fusion system is proposed under the premise of ensuring the traditional state estimator structure, and the generalized polarity is improved at the same time. The combination of the large likelihood (GM) estimation and the estimation fusion system is used to estimate the system node voltage amplitude and phase angle. First, the GM estimation is used to enhance the robustness of the estimation model. By using the adaptive mapping statistics and the GM estimation The weight function of the objective function is analyzed, and the improved GM estimation method is used for state estimation. Secondly, considering the technical differences between the traditional measurement system and the phasor measurement system in terms of measurement channels and instrument sampling rates, based on the traditional state estimator In this paper, the phasor measurement data is fully used to estimate the state of different estimation modules. At the same time, the multi-sensor data fusion theory (MDF) is used to fuse the estimation results to obtain the optimal estimation value. Finally, the improved IEEE 14 and IEEE The simulation analysis of a 33-node distribution network example verifies the effectiveness and reliability of the proposed improved GM estimation and estimation fusion system.

published proceedings

  • Southern Power System Technology

author list (cited authors)

  • Xu, Y., Wang, G., Sun, S., & Lu, M. i.

complete list of authors

  • Xu, Y||Wang, G||Sun, S||Lu, Mi

publication date

  • 2022