Power grid weak link identification method based on Bayesian reasoning

A weak link and identification method technology, applied in the direction of power network operating system integration, electrical components, circuit devices, etc., can solve the problems of identifying the actual power grid, computing power and network adaptability constraints, identification and evaluation objects not covered, etc. , to achieve the effect of reducing the modeling error

Active Publication Date: 2020-11-10
GUIZHOU POWER GRID CO LTD
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  • Description
  • Claims
  • Application Information

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Problems solved by technology

As the complexity of the network further increases, the computing power and network adaptability of methods based on state reliability indicators are often significantly restricted. In recent years, breakthroughs in artificial intelligence algorithms have been proposed based on data-driven and probability analysis methods. The algorithm can meet the computational requirements

Method used

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  • Power grid weak link identification method based on Bayesian reasoning
  • Power grid weak link identification method based on Bayesian reasoning
  • Power grid weak link identification method based on Bayesian reasoning

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Embodiment 1

[0037] The embodiment of the present invention provides a comparison diagram of the power flow topology of a simple power grid and the Bayesian network model proposed by the present invention for auxiliary analysis, such as figure 1 Shown:

[0038] according to figure 1 According to the topological structure of the power grid, the nodes and branches in the network are separated, and the nodes and branches are connected one by one by topological knot lines. According to the real-time running power flow results, the direction of the branch-nodes in the model is determined according to the flow direction. The node points to the end node and obeys the node conditional probability distribution and the joint probability distribution

[0039] figure 1 Middle current slave node X 5 Flow X 3 through the middle node y 5-3 , then the corresponding parent node X in the Bayesian network 5 point to the middle node y 5-3 , satisfying the conditional probability distribution P(y 5-3...

Embodiment 2

[0073] This embodiment takes the IEEE New England 39-node system as an example, and uses MATLAB programming to implement a method for identifying weak links in a power grid based on Bayesian reasoning.

[0074] Table 1 Line Weakness under Multiple Fault Modes

[0075]

[0076] Taking the three lines 13-14, 14-15, and 16-17 in the same power flow direction as an example, in Table 1, π y13-14 , π y14-15 , π y16-17 Respectively represent the weakness of lines 13-14, 14-15, 16-17, the failure mode includes single component failure and multiple failures in the N-1 criterion, O y13 , O y14 , O y16 Indicates that faults occur at nodes 13, 14, and 16 and cause network power flow changes. When multiple faults occur, the vulnerability of the same branch is greatly affected by the electrical distance of the attack point. When the fault range affects the branch, the branch vulnerability The value is relatively high, and the difference between its value and the weak degree under th...

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Abstract

The invention provides a power grid weak link identification method based on Bayesian reasoning, which comprises the following steps: fusing historical load conditions of elements in a power grid withactual operation data, constructing a distribution probability table considering power transmission distribution factors by utilizing data-driven thinking, and establishing a node-branch Bayesian network through tide topology and a grid structure; and initiating a bifurcation attack to the network according to different fault modes, updating the distribution probability table, and calculating theweakness of all branches by using a maximum possible interpretation algorithm. The technical method provided by the invention mainly depends on a network structure and an operation state, and is lessinfluenced by interference of a fault type; the proposed data driving algorithm can meet the calculation requirement of weak identification of a large power grid, and modeling errors are reduced; multiple types of fault events in an actual power grid are covered, and the requirements for power grid operation reliability and planning directivity can be met.

Description

technical field [0001] The invention relates to the technical field of power grid operation, in particular to a method for identifying weak links in a power grid based on Bayesian reasoning. Background technique [0002] In recent years, with the increase in the scale and complexity of large power grids, the failure risk coefficient and safety indicators have also been further improved. Research on how to quickly and effectively identify weak links in the power grid has become an important problem to be solved urgently in operation planning. In the existing research, the identification and estimation of weak links in the power grid are mainly carried out around both nodes and branches in the network. The main methods include grid structure-based indicators, state-based reliability indicators, and probability-based and data-driven methods. . Most of the current studies based on grid structure index methods are oriented towards line vulnerability estimation, using the grid ad...

Claims

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Application Information

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IPC IPC(8): G06F30/18H04L12/24H02J3/00G06Q10/06G06Q50/06
CPCG06F30/18H04L41/145H04L41/12H04L41/06H02J3/00G06Q10/0635H04L41/0631G06Q50/06G06F2113/04H02J2203/10H02J2203/20Y02B70/30Y04S20/20
Inventor 胡江刘文霞蒋泽甫何向刚钟以林龙蔷罗文雲马冲邓朴唐学用张裕
Owner GUIZHOU POWER GRID CO LTD
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