Power system transient stability key feature selection method considering class imbalance

A key feature, power system technology, applied in the field of key feature selection for power system transient stability considering category imbalance, can solve the problems of not considering the imbalance of transient stability assessment, and difficult to meet the actual needs of power grid security and stability analysis. , to achieve the effect of strong identification ability

Inactive Publication Date: 2019-01-11
STATE GRID SICHUAN ELECTRIC POWER CORP ELECTRIC POWER RES INST +1
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Problems solved by technology

Therefore, because the existing transient stability feature selection method does not consider the imbalance of tra

Method used

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  • Power system transient stability key feature selection method considering class imbalance
  • Power system transient stability key feature selection method considering class imbalance
  • Power system transient stability key feature selection method considering class imbalance

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Embodiment

[0037] Such as figure 1 , figure 2 , image 3 , Figure 4 with Figure 5 As shown, the key feature selection method of power system transient stability considering category imbalance;

[0038] Original feature set construction;

[0039] Use the time dimension statistics of the electrical state to construct the original feature set for transient stability assessment, including the power flow state before the fault occurs and the electrical response curve after the fault; the power flow state characteristics mainly include the load level of the system and the output level of the generator and node voltage levels;

[0040] The electrical response characteristics are divided into the instantaneous characteristics of fault occurrence and the characteristics of fault removal time. At the moment of fault occurrence, the generator is subjected to power unbalanced impact, and the generator acceleration and active power impact are used as the instantaneous characteristics of fault...

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Abstract

A method for selecting key features of power system transient stability considering class imbalance includes the following steps: S1, constructing original feature set of transient stability assessment by using time dimension statistics of electrical state; S2, generating a preset number of sample sets; 3, define a weighted accuracy rate CWA of a comprehensive evaluation index category according to an evaluation criterion selecte from transient stability evaluation characteristics; S4, the key features of transient stability assessment are screened by using the encapsulation method which combines forward search and transfinite learning machine. Aiming at the unbalanced characteristics of the transient stability of the power system, the invention proposes two criteria to be satisfied for the selection of the key features, and on the basis of the two criteria, a class weighted accuracy index is proposed as an evaluation index for the selection of the key features. Taking the new evaluation index as the feature selection standard, the key features of transient stability are searched by using the encapsulation method of forward search and transfinite learning machine, and the key features of instability class with higher identification degree are excavated, which meets the actual requirements of power network security and stability analysis.

Description

technical field [0001] The invention relates to the technical field of power system safety and stability analysis, in particular to a method for selecting key features of power system transient stability considering category imbalance. Background technique [0002] In recent years, with the large-scale application of wide-area measurement systems and the rapid development of computer technology, the transient stability assessment of power systems based on artificial intelligence technology has attracted extensive attention from scholars from all over the world. Usually, the transient stability assessment based on artificial intelligence technology is treated as a two-mode classification problem, that is, divided into two categories: stable and unstable. Input features are an important factor affecting the performance of artificial intelligence classification models. Most of the existing feature sets used in transient stability classification are manually selected based on ex...

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Application Information

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IPC IPC(8): H02J3/24H02J3/26
CPCH02J3/24H02J3/26H02J2203/20Y02E40/50
Inventor 陈振韩晓言张华常晓青范成围陈刚史华勃王曦刘畅
Owner STATE GRID SICHUAN ELECTRIC POWER CORP ELECTRIC POWER RES INST
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