A fast and robust state estimation method for power systems

Abstract

The invention provides a method for quickly estimating robust state of a power system. The method is used for dynamically adjusting quantity measuring weight through a factor table increment correction algorithm and includes: step 1, acquiring a Jacobi matrix H of a quantity measuring equation Z of the power system according to a power grid model and data of power transmission section; step 2, performing orthogonal transformation on the Jacobi matrix H to acquire an active iteration upper triangular matrix LP and a reactive iteration upper triangular matrix LQ; step 3, performing active iteration calculation and reactive iteration calculation on the matrixes LP and LQ to acquire a state quantity estimation value and quantity measuring residual; step 4, judging the quantity measuring weight according to the quantity measuring residual sigma, and if weight adjustment is needed, adopting the factor table increment correction algorithm to correct the matrixes LP and LQ and returning back to step 3. Compared with the prior art, the method has the advantages that by combining dynamic weight adjusting technology with the factor table increment correction algorithm, accuracy of state estimation can be improved effectively, and calculating time of state estimation is reduced.

Description

technical field [0001] The invention relates to a method for estimating an error-resistant state, in particular to a method for quickly estimating an error-resistant state of a power system. Background technique [0002] With the construction and development of the smart grid, the scale of the grid is getting larger and larger, and the online analysis and calculation of the power system, especially the state estimation calculation, has brought new challenges. How to improve the calculation accuracy and speed of state estimation and quickly and accurately calculate the real-time operation mode of the entire large power grid, so as to provide accurate and reliable data sources for other power grid analysis applications, has become an urgent technical problem to be solved in the state estimation calculation of ultra-large-scale power systems . [0003] At present, the robust least squares state estimation method has become a state estimation algorithm widely used in power syst...

AI Technical Summary

Problems solved by technology

However, in the actual operation, the weighted Jacobian matrix needs to be re-orthogonally decomposed according to the weight function during the robust iteration process, which greatly reduces the computational efficiency and limits the practicability of the robust least squares state estimation; it mainly includes the following defect:

[0004] ①: Weighted least square method due to H T R -1 / 2 The matrix can be constantized and does not need to be modified during the iterative process, so the calculation speed is fast; while the state estimation of the robust weighted least squares method will dynamically adjust the weight according to the residual error during the iterative process, and it is necessary to regenerate H T R -1 / 2 The L matrix is ​​decomposed into an L matrix orthogonally, which increases the complexity of the calculation and greatly increases the calculation time of the state estimation. Especially when the calculation scale is large, the calculation time increases greatly, which affects the practical progress of this algorithm.

[0005] ②: In each iteration process, the weight measured according to the residual adjustment amount cannot achieve the purpose of robustness and maintaining the calculation efficiency and convergence rate of the algorithm at the same time

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