DMD-based electric power system dominant oscillation mode and parameter recognition method

Abstract

The invention provides a DMD-based electric power system dominant oscillation mode and parameter recognition method. Constructing a power system state equation; discretizing a system state equation byadopting a DMD algorithm; obtaining a discrete system state matrix; the objective of the invention is to prevent redundant information in a discrete system state matrix from affecting a subsequent recognition process early. Converting the calculation of a discrete system state equation into the calculation of a system low-dimensional approximate matrix; calculating the system low-dimensional approximate matrix to obtain a time characteristic parameter and a space characteristic parameter of the power system; Meanwhile, the modal shape of the power system is obtained, the concept of mode energy is provided on the basis of the DMD algorithm, the dominant oscillation mode of the power system is judged by utilizing the amplitude of the mode energy, a theoretical basis is provided for stable operation of the power system, and the method plays an important role in guiding actual operation.

Description

technical field [0001] The invention relates to the technical field of power systems, in particular to a DMD-based power system dominant oscillation mode and parameter identification method. Background technique [0002] Electromechanical oscillation is not only a serious threat to the safe and stable operation of large-scale interconnected power grids, but also one of the key factors that limit the ability of inter-regional power exchange. Monitoring and analyzing electromechanical oscillations in power systems is an important means to ensure the safe and stable operation of power systems . [0003] In the early power system PMU (Phasor Measurement Unit) configuration was less, using advanced signal analysis methods, such as Prony and HHT and single-channel measurement data to extract the frequency and damping ratio, because the generators are coupled to each other through the network, the actual electromechanical The oscillation process, especially the interregional oscil...

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Problems solved by technology

[0003] In the early power system PMU (Phasor Measurement Unit) configuration was less, using advanced signal analysis methods, such as Prony and HHT and single-channel measurement data to extract the frequency and damping ratio, because the generators are coupled to each other through the network, the actual electromechanical The oscillation process, especially the interregional oscillation mode, shows a strong global feature, which is difficult to detect and analyze by simply relying on a single measurement channel. In recent years, with the increase in the number of PMU configurations, domestic and foreign experts and scholars Introduce the dynamic feature extraction method based on multi-channel data sources to analyze dynamic behavior, including the coherent identification method of generator sets based on principal component analysis method; use orthogonal decomposition, multivariate empirical mode decomposition and random space technology to extract data from PMU measurement data Methods for extracting mode frequency, damping ratio and mode shape characteristics, but none of the above methods can effectively extract dynamic features and use them to analyze dynamic behavior

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