A method of power system vulnerability assessment based on high-dimensional stochastic matrix theory

A high-dimensional random matrix and weak point technology, applied in electrical components, circuit devices, AC network circuits, etc., can solve problems such as misjudgment

Active Publication Date: 2019-01-11
THE GENERAL DESIGNING INST OF HUBEI SPACE TECH ACAD
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Problems solved by technology

Liu Wei and others put forward the "Identification Method of Power Grid Weak Links Based on Random Matrix Theory and Entropy Theory" (Proceedings of the Chinese Society for Electrical Engineering, 2017

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  • A method of power system vulnerability assessment based on high-dimensional stochastic matrix theory
  • A method of power system vulnerability assessment based on high-dimensional stochastic matrix theory
  • A method of power system vulnerability assessment based on high-dimensional stochastic matrix theory

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Embodiment Construction

[0062] The present invention will be described in further detail below in conjunction with the accompanying drawings and embodiments.

[0063] First, the basic concepts commonly used in random matrix theory are explained:

[0064] (1) Marchenko-Pastur (M-P) theorem

[0065] The M-P theorem describes the density function of the empirical spectral distribution. Let X={x i,j} is a non-Hermitian random matrix of order N×T (that is, N rows and T columns), and the sample covariance matrix of the random matrix is

[0066] Assume that the elements in the random matrix X are independent and identically distributed, and the mean value μ(x)=0, the variance σ 2 (x)Figure 1a and Figure 1b , when N,T→∞, and the proportional coefficient c=N / T∈(0,1], the sample covariance matrix of the random matrix The empirical spectral distribution of converges to The Marcenko-Pastur Law, that is, the M-P rate, expressed as a density function:

[0067]

[0068] In the formula: lambda s are ...

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Abstract

The invention discloses a power network weak point assessment method based on the high-dimensional random matrix theory. The method comprises the following steps: a node is randomly selected as a disturbed node from the normal operation power network system; a preset time disturbance is applied to the disturbed node in the test time, and voltage data of the power network system operation in the test time is collected; a preset sliding time window is used to truncate the voltage data into a plurality of original data matrices, and based on the original data matrices, an augmented matrix corresponding to each node of the disturbed power system except the disturbed node is constructed. Based on M-P rate, ring rate and linear eigenvalue statistic, the augmented matrix is processed to obtain the empirical spectral distribution and average spectral radius. According to the empirical spectral distribution and average spectral radius value, the comprehensive evaluation index of weak points ofthe disturbed node power network is calculated. By analogy, the other nodes of the power system are calculated as the disturbed nodes to evaluate the weakness of the power system. The method has highaccuracy and can avoid misjudgment.

Description

technical field [0001] The invention relates to the technical field of power grid operation, in particular to a method for evaluating weak points of power grids based on high-dimensional random matrix theory. Background technique [0002] Weak links in the power grid play a key role in the occurrence and expansion of faults, and the identification of key nodes in the power grid has important theoretical and applied research values. [0003] At this stage, there are mainly two types of research methods for power grid vulnerability identification. The first category is based on complex network theory, constructs evaluation indicators according to the topological structure of the power grid, explores the main causes of accidents and evaluates the vulnerability of the power grid. The theory of complex network depends too much on the topological structure of power grid, it is difficult to establish a general model, and there are great limitations. The second category is mainly ...

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Application Information

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IPC IPC(8): H02J3/00
CPCH02J3/00H02J2203/20
Inventor 王佳丽张红张奎程志李朝波蒋传魁陶金王欢郑宇杜鹏
Owner THE GENERAL DESIGNING INST OF HUBEI SPACE TECH ACAD
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