Delayed power system feature value analysis method based on low-order IIGD algorithm

Abstract

The invention discloses a delayed power system feature value analysis method based on a low-order iterative infinitesimal generator discretization (IIGD) algorithm. A linear mathematical model of a delayed power system is built, and a differential equation of the delayed power system is obtained; state variables of the system are divided into delay-independent items and delay-dependent items according to a differential equation of the delayed power system; an infinitesimal generator is subjected to pseudo-spectral discretization, multiple discrete points are taken in the delay interval, a discrete function space is established, only the delay-dependent part is discretized on the discrete function space on the basis of a recombined mathematical model of the delayed system to generate a low-order infinitesimal generator discretized matrix; delayed power system feature values are obtained by adopting a sparse feature value algorithm; and for the obtained delayed power system feature values, the calculated feature values are verified with a Newton method, and if the convergence condition is met, precise feature values and feature vectors of the delayed power system can be obtained.

Description

technical field [0001] The invention relates to the technical field of power systems, in particular to a time-delay power system eigenvalue analysis method based on a low-order IIGD algorithm. Background technique [0002] With the development of the power system and the increasing demand for energy, the traditional power system is facing challenges brought about by the expansion of the system scale and the access to new energy sources. For large-scale interconnected systems, the wide-area measurement system (Wide-Area Measurement System, WAMS) based on the synchrophasor unit (PhasorMeasurement Unit, PMU) can collect the operating data of the modern power system synchronously in real time to help operators realize Wide-area situational awareness provides a new control method for improving the stability of power system operation. [0003] The Wide-Area Damping Controller (WADC) based on WAMS can effectively improve the damping level of the interval low-frequency oscillation ...

AI Technical Summary

Problems solved by technology

These existing analysis methods have their own shortcomings: the time domain method does not need to solve the system equations to directly determine the stability, but it is conservative; the Rekasius transformation in the frequency domain method can only solve the eigenvalues ​​on the imaginary axis, and the frequency domain method The accuracy of the Padé approximation in the method has not been verified on large-scale multi-delay power systems

However, these eigenanalysis methods for time-delay power systems based on spectral discretization have large dimensions of the approximate matrix generated during the discretization process, especially when analyzing large-scale power systems, although the sparse eigenvalue algorithm is used to utilize the system state The sparse nature of the matrix improves the efficiency of the algorithm, but due to the inherent dimensionality problem, it inevitably generates a large amount of calculation and calculation time, which limits the efficiency of the algorithm

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