A power flow iterative calculation method and system based on hybrid preprocessing

CN120675081BActive Publication Date: 2026-07-21WUXI RES INST OF APPLIED TECH TSINGHUA UNIV +1

Patent Information

Authority / Receiving Office: CN · China
Patent Type: Patents(China)
Current Assignee / Owner: WUXI RES INST OF APPLIED TECH TSINGHUA UNIV
Filing Date: 2025-05-09
Publication Date: 2026-07-21

AI Technical Summary

Technical Problem

Existing technologies are insufficient to effectively solve the ill-conditioned power flow calculation problem caused by high R/X ratios, weak grid connections, and voltage instability in large-scale power systems, especially the numerical stability degradation and convergence obstruction caused by the ill-conditioned Jacobian matrix in the Newton-Raphson algorithm.

Method used

A hybrid preprocessing method is adopted, which generates an initial state vector through nonlinear initialization, constructs a Jacobian matrix and performs norm scaling, row and column rearrangement and incomplete decomposition, and combines it with the double conjugate gradient stabilization algorithm to dynamically adjust the residual control strategy, thereby realizing the combination of power grid physical characteristics and numerical preconditioning technology.

Benefits of technology

It improves the numerical stability and convergence of power system simulation, reduces the risk of ill-conditioned power flow calculation, enhances the robustness of Newton's method, and realizes real-time optimization of large-scale time-varying power grids.

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Abstract

The application discloses a power flow iterative calculation method and system based on hybrid preprocessing, and mainly relates to the technical field of data calculation of power systems. The method comprises the following steps: based on the Newton-Krylov subspace power flow calculation basic framework, a linear system corresponding to a Jacobian matrix is constructed; the Jacobian matrix is sequentially subjected to norm scaling, row and column rearrangement and incomplete decomposition to generate a preconditioning operator; the preconditioning operator is embedded into a double conjugate gradient stable algorithm, and a nonlinear solution is updated through dynamic adjustment of a residual error control strategy; and according to the fact that the residual error satisfies the convergence condition of the Newton-Krylov subspace power flow calculation, it is judged whether to terminate the calculation and output the power flow result or to continue iteration. The application has the beneficial effect that it realizes the combination of the physical characteristics of a power grid and the numerical preconditioning technology, and provides a reliable solution for the simulation of a large-scale node power system.

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