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Power system low-frequency oscillation online identification method based on recursive stochastic subspace

A random subspace, low-frequency oscillation technology, applied in electrical components, circuit devices, AC network circuits, etc., can solve problems such as large redundancy, difficulty in online identification engineering, and time-consuming algorithms

Active Publication Date: 2015-10-21
FUZHOU UNIV
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Problems solved by technology

However, this algorithm requires high-order data matrix singular value decomposition (SVD) for each identification, which is time-consuming and redundant. In the application of low-frequency oscillation mode identification in power systems, not only the dynamic identification effect of the oscillation mode is poor, but also Moreover, it is difficult to implement online identification engineering

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  • Power system low-frequency oscillation online identification method based on recursive stochastic subspace
  • Power system low-frequency oscillation online identification method based on recursive stochastic subspace
  • Power system low-frequency oscillation online identification method based on recursive stochastic subspace

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Embodiment Construction

[0042] The technical solution of the present invention will be specifically described below in conjunction with the accompanying drawings.

[0043] An on-line identification method of low-frequency oscillations in power systems based on recursive random subspaces of the present invention, specifically the combination of identification methods and methods for low-frequency oscillations in power systems figure 1 Illustrate and describe the ideal signal of power system low frequency oscillation Superimpose white noise with a signal-to-noise ratio of 10dB, the data sampling time is 0-20 seconds, and the sampling frequency is 20Hz. The method of the invention is used to identify the main information of the oscillation mode. Among them, 5s sampling initialization data is selected to construct the Hankel matrix, and the window data is 0.1s. Specific steps are as follows:

[0044] Step 1: Sampling the discrete time series data by Construct the covariance Hankel matrix:

[0045]...

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Abstract

The invention relates to a power system low-frequency oscillation online identification method based on a recursive stochastic subspace. According to the method, in order to solve the problem that the real-time performance and dynamic identification effect of low-frequency oscillation modal identification are poor due to the need of SVD decomposition with high algorithm complexity in a stochastic subspace identification algorithm, a forgetting factor is introduced to update a Hankel covariance matrix, and a projection approximation subspace tracking method is used to perform recursive operation on the subspace. Thus, SVD operation is avoided, and the computational complexity is reduced significantly. In each recursive calculation, the complexity of the algorithm of the invention is 3In+O(I<2>), which is far lower than O(I<3>), the complexity of SVD calculation. By adopting the method of the invention, the real-time performance of identification can be improved effectively. The invention is suitable for online identification of low-frequency oscillation modal, and can provide effective support for power system online monitoring and stability analysis under multiple spatial and temporal scales.

Description

technical field [0001] The invention relates to the technical field of power system low-frequency oscillation analysis, in particular to an online identification method for power system low-frequency oscillation based on a recursive random subspace. Background technique [0002] With the interconnection of large-scale power systems and the grid-connected operation of large-scale wind and photovoltaic power generation systems and their increasing proportion in the installed capacity of the grid, the problem of weakly damped low-frequency oscillations in the grid has become increasingly prominent, seriously affecting the stable operation of the grid and power quality control. Real-time and accurate identification of each modal information of the oscillation, positioning the oscillation area and the unit, and then applying effective low-frequency oscillation suppression measures are extremely critical. At present, the wide application of wide area measurement system (WAMS), esp...

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): H02J3/00G06F19/00
Inventor 金涛仲启树
Owner FUZHOU UNIV
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