A fractal-based main distribution network collaborative robust state estimation method and device

By correcting pseudo-measurements using fractal features and combining boundary coordination and robust weights, the iterative solution of the Krawczyk-Moore algorithm is improved. This solves the problems of unreasonable pseudo-measurement intervals and non-adaptive boundary constraints in the main distribution network coordinated state estimation, thereby improving the accuracy and convergence of distribution network state estimation.

CN122801208APending Publication Date: 2026-09-22TIANJIN UNIV +1
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Patent Information

Application Number
CN202610715437.6
Authority / Receiving Office
CN · China
Patent Type
Applications(China)
Current Assignee / Owner
Filing Date
2026-05-22
Publication Date
2026-09-22

AI Technical Summary

Technical Problem

Existing main-distribution coordinated state estimation techniques suffer from problems such as unreasonable pseudo-measurement intervals, non-adaptive boundary constraints, poor interval robustness, and excessive interval envelope, resulting in insufficient accuracy and convergence in distribution network state estimation.

Method used

By collecting raw measurement data from the main grid and distribution network, and combining fractal characteristics and feeder depth for correction, boundary voltage consistency and power conservation constraints are constructed. Robust weights are introduced, and an improved Krawczyk-Moore algorithm is used for iterative solution to alleviate the problem of excessive envelope in the interval.

Benefits of technology

It improves the accuracy and convergence of distribution network state estimation, ensures the robustness and stability of the estimation results, adapts to the load fluctuation characteristics of different nodes, and achieves high-quality state estimation.

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Abstract

This invention discloses a fractal-based method and apparatus for estimating the cooperative robust state of a main and distribution network. The method collects raw measurement data from the main and distribution networks, combines fractal characteristics with feeder depth correction, and generates a unified input interval measurement for main-distribution cooperative state estimation. Based on this input measurement, a main-distribution boundary coordination relationship is constructed through boundary voltage consistency and power conservation constraints. The distribution network state interval is initially narrowed using high-reliability boundary information from the main network. An interval deviation index between the measurement interval and the estimation interval is calculated, and robustness weights are allocated accordingly to suppress abnormal pseudo-measurement interference. Based on the robustness weights and the initially narrowed state interval, a unified main-distribution cooperative state estimation model is constructed. The excessive envelope of the interval is alleviated through affine approximation of error propagation, and the improved Krawczyk-Moore algorithm is used for iterative solution to obtain the main-distribution cooperative robust state estimation result. This invention solves the problems of unreasonable pseudo-measurement intervals and non-adaptive boundary constraints in existing technologies.
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